#python -m spacy download en_core_web_lg

import spacy
nlp = spacy.load("en_core_web_lg")
from spacy.lang.en import STOP_WORDS 

import re
import unicodedata

import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.linear_model import LogisticRegression
from sklearn.svm import SVC
from sklearn.metrics import classification_report, accuracy_score, precision_score, recall_score, f1_score, confusion_matrix, roc_auc_score
from sklearn.feature_selection import RFE, SelectKBest, chi2

from tqdm import tqdm
from math import log

from imblearn.over_sampling import RandomOverSampler
from collections import Counter

import datetime

def counter(word):
    global df_model
    return df_model[word].sum()

def make_list(input_string):
        '''creates a list of chars form given string'''
        char_list = []
        for l in input_string:
            char_list.append(l)
        return char_list
    
def make_dict(input_string):
        '''creates a dictionary of unique words used in text, with frequency as value'''
        words_dict = dict()
        temp_list = input_string.split()
        for item in temp_list:
            if item not in words_dict:
                words_dict[item] = 1
            else:
                words_dict[item] += 1
        return words_dict

def prepare_string(input_string):
    global if_dict, master_dict, error_dict, failed_error_dict, stopwords,failed_scrabble, failed_words, total_words, failed_to_lemmatize, scrabble_words, lemmatized_1st, lemmatized_2nd, lemmatized_3rd
    # 1. Convert to lowercase
    lowercase_string = input_string.lower()
    # 2. Exclude everything except letters and spaces and "-"
    prelemma_string = ""
    spacing = True
    for char in lowercase_string:
        if char in let_low:
            spacing = True
            prelemma_string += char
        elif (char == ' ' or char=='\n'):
            if spacing == True:
                prelemma_string += " "
                spacing = False
        else:
            spacing = False
    
    # 3. Perform lemmatization
    doc = nlp(prelemma_string)
    lemmatized_string = ""
    for token in doc: 
        success = False
        total_words += 1
        
         #1st instance --> spacy's lemmatization
        if token.has_vector and ignore_stopwords == False:
            lemmatized_string += token.lemma_.lower() + " "
            lemmatized_1st.append(token.text + " --> " + token.lemma_)
            success = True 
        if token.has_vector and ignore_stopwords == True:
            if token.text not in STOP_WORDS:
                lemmatized_string += token.lemma_.lower() + " "
                lemmatized_1st.append(token.text + " --> " + token.lemma_)
                success = True
            if token.text in STOP_WORDS:
                success = True
            
        #2nd instance --> common error vocabulary:
        if success == False:
            if token.text in error_dict:
                temp_token = nlp(error_dict[token.text])
                for tok in temp_token:
                    if tok.has_vector and ignore_stopwords == False:
                        lemmatized_string += tok.lemma_.lower() + " "
                        lemmatized_2nd.append(token.text + "-->" + tok.lemma_.lower())
                        success = True
                    if tok.has_vector and ignore_stopwords == True:
                        if tok.lemma_ not in STOP_WORDS:
                            lemmatized_string += tok.lemma_.lower() + " "
                            lemmatized_2nd.append(token.text + "-->" + tok.lemma_.lower())
                            success = True
                        if tok.lemma_ in STOP_WORDS:
                            success = True
                    if tok.has_vector == False: #being in predefined error dictionary but failed to lemmatize by spacy
                        failed_error_dict.append(tok.text.lower()) 
        #if everything above fails add words to the dictionary of unnlemmatized    
        if success == False: 
                if ignore_stopwords == False:
                    lemmatized_string += "#failed" + " "
                    failed_words += 1
                    if token.text in failed_to_lemmatize:
                        failed_to_lemmatize[token.text] += 1
                    else:
                        failed_to_lemmatize[token.text] = 1
                if ignore_stopwords == True and token.lemma_ not in STOP_WORDS:
                    lemmatized_string += "#failed" + " "
                    failed_words += 1
                    if token.text in failed_to_lemmatize:
                        failed_to_lemmatize[token.text] += 1
                    else:
                        failed_to_lemmatize[token.text] = 1
    
    #using a previous master dictionary (option for target set):
    if if_dict == True:
        to_check = lemmatized_string.split()
        in_dict = []
        for word in to_check:
            if word in master_dict or word=='#failed':
                in_dict.append(word.lower())
            else:
                in_dict.append('#unique')
        new_lemmatized_string = ' '.join(in_dict)
    
    if if_dict == False:
        new_lemmatized_string = lemmatized_string
                
    return new_lemmatized_string.lower()

def make_dict_from_column(df_column):
    '''creates a sorted dictionary of unique words used in whole dataframe column, values are lists, first'''
    words_dict = dict()
    for row_value in df_column:
        temp_list = row_value.split()
        for item in temp_list:
            if item not in words_dict:
                words_dict[item] = 1
            else:
                words_dict[item] += 1 
        
    return dict(sorted(words_dict.items()))

def how_many_cases(word,df_column):
    '''count how many rows include the word'''
    num = 0
    for item in df_column:
        if word in item:
            num += 1
    return num    

def create_score_column(base, key, count_column, method, v_neg, idf_all,idf_word):
    '''Creates a column with given values
        base - dictionary to look up words /dictionary
        key - word to check  /string
        count_column - from which columnn /string
        method - hyperparamether / string (binary,count,frequency or TF)
        v_neg - value if negative /integer or formula
    '''
    if method == "binary" and key in base:
        return 1
    if method == "count" and key in base:
        return base[key]
    if method == "frequency" and key in base:
        return (base[key]/count_column)
    if method == "IDF" and key in base:
        return (1+log(idf_all/idf_word))
    if method == "TFIDF"and key in base:
        return (base[key]/count_column)*(1+log(idf_all/idf_word))
    if key not in base:
        return v_neg
    

def word_counter(dict):
    '''Counts words in a dictionary'''
    count = 0
    for key in dict:
        if key != '#stop': #ignore stopwords
            count += dict[key]
    return count

def failed_count(dict):
    '''Count words failed to lemmatize'''
    if "#failed" in dict.keys(): 
        return dict['#failed']
    else:
        return 0 

def unique_count(dict):
    '''Counts unique words'''
    if "#unique" in dict.keys(): 
        return dict['#unique']
    else:
        return 0 

def standarize(value,maximum):
    ''' '''
    if value == 1:
        return 0
    elif value > 1:
        return (value - 1)/(maximum - 1)
    elif value < 1:
        return (value - 1)
    else:
        return None

def check_similarity(txt):
    '''Checks whether given text is similar to any item in the list. List and cut off defined globally'''
    global doc_sim_list
    global similarity_cut_off
    doc1 = nlp(txt)
    for item in doc_sim_list:
        if (doc1.similarity(item) >= similarity_cut_off):
            return 1     
    return 0
        
#Global variables:
failed_to_lemmatize = dict()
failed_words = 0
total_words = 0 
failed_error_dict = []
lemmatized_1st = []
lemmatized_2nd = []
master_dict = dict()

let_low = make_list("weęrtyuioópaąsśdfghjklłzżxźcćvbnńmq-") # list of possible chars
#Instance 2 vocabulary:
fin = open('error_dict.txt', encoding="utf8")
error_dict = dict() #dict for correcting common mistakes by customers
for line in fin:
    text = line.split(":")
    error_dict[text[0]] = text[1]

pd.options.display.max_columns = 50

#HYPERPARAMETRES:
#Sets:
init_set = "df_nlp_teacher.csv"
target_set = "df_nlp_student.csv"
desc_column_name = 'text' 
target_column_name = '#fraudulent'

#NLP:
score_type = "TFIDF" #binary,count,frequency, IDF or TFIDF
ignore_stopwords = True #if true stopwords won't be lemmatized
similarity_cut_off = 0.99 #value for scoring the similarity variable

#Data processing and choosing variables:
min_words = 0 #cases not meeting the requirement will be cut out of training set (rows)
fraud_only = False #if True columns will be limited to words appearing only in target class
low_cut = False #if True words not meeting the requirement will be cut out of set (columns)
at_least = 2
oversample = True
over_proportion = 10 #denominator value of classification proportion, 2 -> 50%, 10 --> 10%, 20 -> 5% etc. 
if_k_best = True
how_much_var = 5000

#Training models
lr_search = False #if True optimizing parameters for logreg model will be performed 
scoring_lr = 'recall'
param_grid_lr = {'C' : [0.1,1,10,100],
             'penalty' : ['l1','l2','none']}
svm_search = False #if True optimizing parameters for logreg model will be permofrmed 
scoring_svm = 'recall'
param_grid = {'C' : [0.1,1,10,100],
             'kernel' : ['linear','rbf'],
             'gamma' : ['scale','auto']}

#Parameters if false:
lr_c = 100
lr_penalty = 'l2'
svm_c = 100
svm_kernel = 'linear'
svm_gamma = 'scale'

#Opening inital and target sets in pandas:

df_init=pd.read_csv(init_set, index_col=0, sep=";", encoding="utf-8")
df_target=pd.read_csv(target_set, index_col=0, sep=";", encoding="utf-8")
drop_list_init = []
for column in df_init.columns:
    if column != desc_column_name and column != target_column_name:
        drop_list_init.append(column)

df_for_nlp = df_init.drop(drop_list_init, axis = 1)

drop_list_target = []
for column in df_target.columns:
    if column != desc_column_name and column != target_column_name:
        drop_list_target.append(column)

df_nlp_score = df_target.drop(drop_list_target, axis = 1)
    
#Lemmatizing, creating dictionaries (incuding master), calculating words and error percentage for each observation:
print('Working on initial set:')
tqdm.pandas(desc="Lemmatizing")
if_dict = False
df_for_nlp['description_lemmatized'] = df_for_nlp[desc_column_name].progress_apply(prepare_string)
tqdm.pandas(desc="Creating Dictionaries")
df_for_nlp['dict']=df_for_nlp['description_lemmatized'].progress_apply(make_dict)
tqdm.pandas(desc="Counting words")
df_for_nlp['word_count'] = df_for_nlp['dict'].progress_apply(word_counter)
tqdm.pandas(desc="Computing percentage of unlemmatized words")
df_for_nlp['failed'] = df_for_nlp['dict'].progress_apply(failed_count)
df_for_nlp['failed_perc']=(df_for_nlp['failed']/df_for_nlp['word_count'])*100
df_post_nlp = df_for_nlp.drop(['failed','description_lemmatized'], axis=1)
#Creating master dict:
master_dict = make_dict_from_column(df_for_nlp['description_lemmatized'])
if '#failed' in master_dict:
    del master_dict['#failed']
#Printing lemma report:
print('INITIAL SET LEMMA REPORT:')
print('failed to lemmatize {}%'.format(((failed_words/total_words)*100)))
print('Total unlemmatized words - {}'.format(len(failed_to_lemmatize)))
print('There are {} unique words in master dictionary. Sum of lemmatized words: {}'.format(len(master_dict),sum(master_dict.values())))

#saving master dictionary and failed words dictionary:
df_master = pd.DataFrame(list(master_dict.items()))
df_master.reset_index()
df_master.to_csv('master.csv', encoding='utf-8')
df_failed = pd.DataFrame(list(failed_to_lemmatize.items()))
df_failed.reset_index()
df_failed.to_csv('failed.csv', encoding='utf-8')

#Reseting blogal variables:
failed_to_lemmatize = dict()
failed_words = 0
total_words = 0 
failed_scrabble = []
lemmatized_1st = []
lemmatized_2nd = []

print('Working on target set:')
tqdm.pandas(desc="Lemmatizing")
if_dict = True
df_nlp_score['description_lemmatized'] = df_nlp_score[desc_column_name].progress_apply(prepare_string)
tqdm.pandas(desc="Creating Dictionaries")
df_nlp_score['dict']=df_nlp_score['description_lemmatized'].progress_apply(make_dict)
tqdm.pandas(desc="Counting words")
df_nlp_score['word_count'] = df_nlp_score['dict'].progress_apply(word_counter)
tqdm.pandas(desc="Computing percentage of unlemmatized words:")
df_nlp_score['failed'] = df_nlp_score['dict'].progress_apply(failed_count)
df_nlp_score['failed_perc']=(df_nlp_score['failed']/df_nlp_score['word_count'])*100
tqdm.pandas(desc="Computing percentage of unique words")
df_nlp_score['unique'] = df_nlp_score['dict'].progress_apply(unique_count)
df_nlp_score['unique_perc']=(df_nlp_score['unique']/df_nlp_score['word_count'])*100
df_sim_teacher = df_init[df_init['#fraudulent']==1]
sim_list = df_sim_teacher['text'].tolist()
doc_sim_list = []
for item in sim_list:
    doc_sim_list.append(nlp(item))
tqdm.pandas(desc="Checking for similarity by given level: "+str(similarity_cut_off*100)+"%" )
df_target['is_similar']=df_target[desc_column_name].progress_apply(check_similarity)
df_target = df_target.drop(desc_column_name, axis=1)

df_nlp_score = df_nlp_score.drop(['failed','unique','description_lemmatized'], axis=1)

#Printing lemma report:
print('TARGET SET LEMMA REPORT:')
print('failed to lemmatize {}%'.format(((failed_words/total_words)*100)))
print('Total unlemmatized words - {}'.format(len(failed_to_lemmatize)))

Working on initial set:

Lemmatizing: 100%|██████████| 8940/8940 [29:59<00:00,  4.97it/s]
Creating Dictionaries: 100%|██████████| 8940/8940 [00:01<00:00, 6418.87it/s]
Counting words: 100%|██████████| 8940/8940 [00:00<00:00, 31595.35it/s]
Computing percentage of unlemmatized words: 100%|██████████| 8940/8940 [00:00<00:00, 144228.41it/s]

INITIAL SET LEMMA REPORT:
failed to lemmatize 14.319979224432583%
Total unlemmatized words - 168137
There are 15290 unique words in master dictionary. Sum of lemmatized words: 1489278
Working on target set:

Lemmatizing: 100%|██████████| 8940/8940 [29:10<00:00,  5.11it/s]
Creating Dictionaries: 100%|██████████| 8940/8940 [00:01<00:00, 5936.52it/s]
Counting words: 100%|██████████| 8940/8940 [00:00<00:00, 28840.09it/s]
Computing percentage of unlemmatized words:: 100%|██████████| 8940/8940 [00:00<00:00, 194366.95it/s]
Computing percentage of unique words: 100%|██████████| 8940/8940 [00:00<00:00, 186260.72it/s]
Checking for similarity by given level: 99.0%: 100%|██████████| 8940/8940 [37:29<00:00,  3.97it/s] 

TARGET SET LEMMA REPORT:
failed to lemmatize 14.27261326922394%
Total unlemmatized words - 167447

#Preparing sets for modelling purposes:
print('Scoring initial set:',end="")
for master_key in tqdm(master_dict):
    idf_all = len(df_post_nlp)
    idf_word = how_many_cases(master_key,df_post_nlp['dict'])
    df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
print('Scoring target set:',end="")
for master_key in tqdm(master_dict):
    idf_all = len(df_nlp_score)
    idf_word = how_many_cases(master_key,df_nlp_score['dict'])
    df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)

#dictionary column is no longer needed, and initial data processing: 
df_post_nlp = df_post_nlp.drop('dict', axis=1)
df_target = df_target.join(df_nlp_score[['failed_perc','unique_perc','word_count']])


nlp_target = df_nlp_score[target_column_name]
df_nlp_score = df_nlp_score.drop([target_column_name,'dict','word_count','failed_perc','unique_perc',desc_column_name], axis=1)

model_to_limit = df_post_nlp['word_count']
model_X = df_post_nlp.drop([target_column_name,'failed_perc','word_count',desc_column_name], axis=1)                   
model_Y = df_post_nlp[target_column_name]

Scoring initial set:

  1%|          | 94/15290 [00:02<05:41, 44.46it/s] C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 99/15290 [00:02<05:40, 44.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 104/15290 [00:02<05:37, 45.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 109/15290 [00:02<05:34, 45.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 114/15290 [00:02<05:36, 45.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 119/15290 [00:03<05:35, 45.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 124/15290 [00:03<05:44, 43.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 129/15290 [00:03<05:39, 44.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 134/15290 [00:03<05:36, 45.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 139/15290 [00:03<05:39, 44.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 144/15290 [00:03<05:44, 43.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 149/15290 [00:03<05:43, 44.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 154/15290 [00:03<05:45, 43.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 159/15290 [00:03<05:43, 44.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 164/15290 [00:04<05:45, 43.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 169/15290 [00:04<05:46, 43.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 174/15290 [00:04<05:50, 43.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 179/15290 [00:04<05:46, 43.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 184/15290 [00:04<05:43, 43.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 189/15290 [00:04<05:41, 44.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 194/15290 [00:04<06:36, 38.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 198/15290 [00:04<06:37, 38.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 203/15290 [00:05<06:24, 39.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 208/15290 [00:05<06:40, 37.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 213/15290 [00:05<06:26, 38.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 218/15290 [00:05<06:10, 40.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 223/15290 [00:05<06:01, 41.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 228/15290 [00:05<05:55, 42.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 233/15290 [00:05<05:48, 43.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 238/15290 [00:05<05:46, 43.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 243/15290 [00:05<05:46, 43.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 248/15290 [00:06<05:53, 42.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 253/15290 [00:06<05:49, 43.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 258/15290 [00:06<06:00, 41.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 263/15290 [00:06<06:00, 41.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 268/15290 [00:06<05:56, 42.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 273/15290 [00:06<05:50, 42.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 278/15290 [00:06<05:49, 42.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 283/15290 [00:06<05:54, 42.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 288/15290 [00:07<05:48, 43.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 293/15290 [00:07<05:49, 42.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 298/15290 [00:07<05:40, 44.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 303/15290 [00:07<05:39, 44.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 308/15290 [00:07<05:39, 44.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 313/15290 [00:07<05:42, 43.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 318/15290 [00:07<05:40, 43.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 323/15290 [00:07<05:54, 42.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 328/15290 [00:07<05:49, 42.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 333/15290 [00:08<06:01, 41.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 338/15290 [00:08<06:06, 40.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 343/15290 [00:08<06:08, 40.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 348/15290 [00:08<06:11, 40.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 353/15290 [00:08<06:11, 40.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 358/15290 [00:08<06:09, 40.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 363/15290 [00:08<06:05, 40.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 368/15290 [00:08<06:06, 40.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 373/15290 [00:09<06:18, 39.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 378/15290 [00:09<06:17, 39.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 382/15290 [00:09<06:24, 38.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 387/15290 [00:09<06:10, 40.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 392/15290 [00:09<06:01, 41.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 397/15290 [00:09<05:52, 42.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 402/15290 [00:09<05:51, 42.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 407/15290 [00:09<05:50, 42.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 412/15290 [00:10<05:49, 42.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 417/15290 [00:10<05:54, 41.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 422/15290 [00:10<06:00, 41.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 427/15290 [00:10<06:01, 41.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 432/15290 [00:10<06:11, 39.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 437/15290 [00:10<06:10, 40.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 442/15290 [00:10<06:13, 39.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 446/15290 [00:10<06:25, 38.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 450/15290 [00:10<06:24, 38.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 455/15290 [00:11<06:15, 39.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 459/15290 [00:11<06:14, 39.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 463/15290 [00:11<06:15, 39.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 467/15290 [00:11<06:23, 38.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 471/15290 [00:11<06:26, 38.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 476/15290 [00:11<06:18, 39.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 481/15290 [00:11<06:11, 39.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 486/15290 [00:11<06:06, 40.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 491/15290 [00:12<05:56, 41.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 496/15290 [00:12<05:49, 42.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 501/15290 [00:12<05:41, 43.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 506/15290 [00:12<05:41, 43.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 511/15290 [00:12<05:35, 44.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 516/15290 [00:12<05:35, 44.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 521/15290 [00:12<05:35, 43.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 526/15290 [00:12<05:45, 42.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 531/15290 [00:12<05:39, 43.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 536/15290 [00:13<05:36, 43.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 541/15290 [00:13<05:34, 44.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 546/15290 [00:13<05:33, 44.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 551/15290 [00:13<05:50, 42.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 556/15290 [00:13<05:53, 41.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 561/15290 [00:13<05:52, 41.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 566/15290 [00:13<06:25, 38.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 571/15290 [00:13<06:20, 38.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 576/15290 [00:14<06:12, 39.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 581/15290 [00:14<06:01, 40.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 586/15290 [00:14<06:06, 40.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 591/15290 [00:14<06:02, 40.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 596/15290 [00:14<06:06, 40.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 601/15290 [00:14<06:07, 39.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 606/15290 [00:14<06:07, 39.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 611/15290 [00:14<07:35, 32.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 616/15290 [00:15<07:03, 34.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 621/15290 [00:15<06:36, 36.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 626/15290 [00:15<06:22, 38.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 631/15290 [00:15<06:04, 40.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 636/15290 [00:15<05:53, 41.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 641/15290 [00:15<05:46, 42.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 646/15290 [00:15<05:41, 42.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 651/15290 [00:15<05:38, 43.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 656/15290 [00:16<05:38, 43.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 661/15290 [00:16<05:44, 42.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 666/15290 [00:16<05:37, 43.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 671/15290 [00:16<05:34, 43.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 676/15290 [00:16<05:47, 42.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 681/15290 [00:16<05:39, 43.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 686/15290 [00:16<05:39, 43.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 691/15290 [00:16<05:48, 41.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 696/15290 [00:16<05:44, 42.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 701/15290 [00:17<05:37, 43.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 706/15290 [00:17<05:35, 43.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 711/15290 [00:17<05:41, 42.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 716/15290 [00:17<05:44, 42.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 721/15290 [00:17<05:39, 42.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 726/15290 [00:17<05:35, 43.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 731/15290 [00:17<05:31, 43.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 736/15290 [00:17<05:32, 43.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 741/15290 [00:17<05:34, 43.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 746/15290 [00:18<05:28, 44.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 751/15290 [00:18<05:28, 44.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 756/15290 [00:18<05:42, 42.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 761/15290 [00:18<05:38, 42.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 766/15290 [00:18<05:42, 42.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 771/15290 [00:18<05:46, 41.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 776/15290 [00:18<05:57, 40.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 781/15290 [00:18<05:59, 40.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 786/15290 [00:19<06:00, 40.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 791/15290 [00:19<06:02, 40.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 796/15290 [00:19<06:05, 39.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 800/15290 [00:19<06:11, 39.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 805/15290 [00:19<06:01, 40.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 810/15290 [00:19<05:58, 40.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 815/15290 [00:19<05:58, 40.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 820/15290 [00:19<05:51, 41.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 825/15290 [00:20<05:50, 41.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 830/15290 [00:20<05:44, 41.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 835/15290 [00:20<05:41, 42.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 840/15290 [00:20<05:36, 42.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 845/15290 [00:20<05:36, 42.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 850/15290 [00:20<05:36, 42.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 855/15290 [00:20<05:36, 42.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 860/15290 [00:20<05:36, 42.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 865/15290 [00:20<05:37, 42.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 870/15290 [00:21<05:37, 42.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 875/15290 [00:21<05:40, 42.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 880/15290 [00:21<05:46, 41.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 885/15290 [00:21<05:47, 41.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 890/15290 [00:21<05:44, 41.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 895/15290 [00:21<05:41, 42.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 900/15290 [00:21<05:36, 42.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 905/15290 [00:21<05:41, 42.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 910/15290 [00:22<05:39, 42.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 915/15290 [00:22<05:45, 41.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 920/15290 [00:22<05:56, 40.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 925/15290 [00:22<05:59, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 930/15290 [00:22<06:09, 38.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 935/15290 [00:22<05:59, 39.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 940/15290 [00:22<05:54, 40.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 945/15290 [00:22<05:47, 41.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 950/15290 [00:23<05:54, 40.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 955/15290 [00:23<05:57, 40.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 960/15290 [00:23<06:07, 38.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 964/15290 [00:23<06:10, 38.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 969/15290 [00:23<06:04, 39.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 974/15290 [00:23<05:58, 39.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 978/15290 [00:23<06:01, 39.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 983/15290 [00:23<05:47, 41.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 988/15290 [00:24<05:49, 40.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 993/15290 [00:24<05:49, 40.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 998/15290 [00:24<05:49, 40.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1003/15290 [00:24<05:51, 40.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1008/15290 [00:24<05:55, 40.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1013/15290 [00:24<05:52, 40.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1018/15290 [00:24<05:53, 40.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1023/15290 [00:24<05:44, 41.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1028/15290 [00:24<05:47, 41.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1033/15290 [00:25<05:44, 41.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1038/15290 [00:25<05:42, 41.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1043/15290 [00:25<05:43, 41.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1048/15290 [00:25<05:52, 40.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1053/15290 [00:25<05:53, 40.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1058/15290 [00:25<05:55, 39.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1063/15290 [00:25<05:57, 39.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1068/15290 [00:25<05:52, 40.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1073/15290 [00:26<05:52, 40.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1078/15290 [00:26<05:51, 40.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1083/15290 [00:26<05:49, 40.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1088/15290 [00:26<05:52, 40.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1093/15290 [00:26<05:48, 40.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1098/15290 [00:26<05:46, 40.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1103/15290 [00:26<05:41, 41.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1108/15290 [00:26<05:39, 41.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1113/15290 [00:27<05:49, 40.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1118/15290 [00:27<05:47, 40.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1123/15290 [00:27<05:48, 40.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1128/15290 [00:27<05:59, 39.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1133/15290 [00:27<05:50, 40.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1138/15290 [00:27<05:49, 40.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1143/15290 [00:27<05:48, 40.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1148/15290 [00:27<05:47, 40.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1153/15290 [00:28<05:43, 41.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1158/15290 [00:28<05:36, 41.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1163/15290 [00:28<05:33, 42.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1168/15290 [00:28<05:33, 42.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1173/15290 [00:28<05:41, 41.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1178/15290 [00:28<05:46, 40.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1183/15290 [00:28<05:44, 40.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1188/15290 [00:28<05:36, 41.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1193/15290 [00:29<05:28, 42.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1198/15290 [00:29<05:26, 43.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1203/15290 [00:29<05:27, 43.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1208/15290 [00:29<05:27, 42.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1213/15290 [00:29<05:29, 42.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1218/15290 [00:29<05:28, 42.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1223/15290 [00:29<05:23, 43.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1228/15290 [00:29<05:20, 43.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1233/15290 [00:29<05:19, 43.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1238/15290 [00:30<05:19, 44.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1243/15290 [00:30<05:19, 43.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1248/15290 [00:30<05:18, 44.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1253/15290 [00:30<05:19, 43.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1258/15290 [00:30<05:16, 44.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1263/15290 [00:30<05:22, 43.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1268/15290 [00:30<05:18, 44.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1273/15290 [00:30<05:17, 44.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1278/15290 [00:30<05:15, 44.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1283/15290 [00:31<05:15, 44.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1288/15290 [00:31<05:18, 43.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1293/15290 [00:31<05:17, 44.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1298/15290 [00:31<05:46, 40.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1303/15290 [00:31<05:43, 40.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1308/15290 [00:31<05:34, 41.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1313/15290 [00:31<05:30, 42.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1318/15290 [00:31<05:27, 42.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1323/15290 [00:32<05:28, 42.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1328/15290 [00:32<05:23, 43.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1333/15290 [00:32<05:23, 43.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1338/15290 [00:32<05:21, 43.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1343/15290 [00:32<05:34, 41.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1348/15290 [00:32<05:37, 41.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1353/15290 [00:32<05:32, 41.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1358/15290 [00:32<05:24, 42.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1363/15290 [00:32<05:18, 43.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1368/15290 [00:33<05:21, 43.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1373/15290 [00:33<05:32, 41.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1378/15290 [00:33<05:35, 41.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1383/15290 [00:33<05:39, 40.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1388/15290 [00:33<05:44, 40.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1393/15290 [00:33<05:46, 40.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1398/15290 [00:33<05:58, 38.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1402/15290 [00:33<05:55, 39.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1406/15290 [00:34<05:54, 39.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1411/15290 [00:34<05:45, 40.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1416/15290 [00:34<05:49, 39.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1420/15290 [00:34<05:53, 39.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1425/15290 [00:34<05:44, 40.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1430/15290 [00:34<05:33, 41.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1435/15290 [00:34<05:41, 40.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1440/15290 [00:34<05:41, 40.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1445/15290 [00:34<05:37, 41.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1450/15290 [00:35<05:36, 41.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1455/15290 [00:35<05:30, 41.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1460/15290 [00:35<05:29, 41.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1465/15290 [00:35<05:35, 41.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1470/15290 [00:35<05:28, 42.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1475/15290 [00:35<05:26, 42.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1480/15290 [00:35<05:21, 42.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1485/15290 [00:35<05:20, 43.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1490/15290 [00:36<05:22, 42.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1495/15290 [00:36<05:21, 42.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1500/15290 [00:36<05:18, 43.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1505/15290 [00:36<05:14, 43.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1510/15290 [00:36<05:14, 43.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1515/15290 [00:36<05:13, 43.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1520/15290 [00:36<05:11, 44.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1525/15290 [00:36<05:11, 44.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1530/15290 [00:36<05:12, 43.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1535/15290 [00:37<05:14, 43.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1540/15290 [00:37<05:15, 43.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1545/15290 [00:37<05:16, 43.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1550/15290 [00:37<05:21, 42.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1555/15290 [00:37<05:22, 42.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1560/15290 [00:37<05:19, 43.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1565/15290 [00:37<05:15, 43.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1570/15290 [00:37<05:16, 43.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1575/15290 [00:37<05:19, 42.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1580/15290 [00:38<05:17, 43.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1585/15290 [00:38<05:22, 42.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1590/15290 [00:38<05:34, 41.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1595/15290 [00:38<05:37, 40.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1600/15290 [00:38<05:29, 41.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1605/15290 [00:38<05:28, 41.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1610/15290 [00:38<05:41, 40.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1615/15290 [00:39<06:09, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1620/15290 [00:39<05:54, 38.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1625/15290 [00:39<05:44, 39.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1630/15290 [00:39<05:45, 39.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1634/15290 [00:39<05:53, 38.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1638/15290 [00:39<05:59, 37.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1643/15290 [00:39<05:49, 38.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1647/15290 [00:39<05:52, 38.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1651/15290 [00:39<05:55, 38.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1656/15290 [00:40<05:42, 39.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1661/15290 [00:40<05:35, 40.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1666/15290 [00:40<05:34, 40.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1671/15290 [00:40<05:32, 40.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1676/15290 [00:40<05:30, 41.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1681/15290 [00:40<05:30, 41.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1686/15290 [00:40<05:24, 41.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1691/15290 [00:40<05:37, 40.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1696/15290 [00:41<05:47, 39.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1700/15290 [00:41<05:52, 38.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1704/15290 [00:41<06:05, 37.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1708/15290 [00:41<06:14, 36.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1712/15290 [00:41<06:15, 36.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1716/15290 [00:41<06:19, 35.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1720/15290 [00:41<06:17, 35.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1725/15290 [00:41<05:58, 37.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1730/15290 [00:41<05:48, 38.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1735/15290 [00:42<05:40, 39.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1740/15290 [00:42<05:42, 39.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1745/15290 [00:42<05:34, 40.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1750/15290 [00:42<05:35, 40.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1755/15290 [00:42<05:33, 40.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1760/15290 [00:42<05:38, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1765/15290 [00:42<05:30, 40.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1770/15290 [00:42<05:26, 41.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1775/15290 [00:43<05:26, 41.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1780/15290 [00:43<05:29, 40.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1785/15290 [00:43<05:30, 40.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1790/15290 [00:43<05:40, 39.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1794/15290 [00:43<05:56, 37.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1798/15290 [00:43<05:56, 37.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1802/15290 [00:43<05:52, 38.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1806/15290 [00:43<05:53, 38.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1810/15290 [00:43<05:56, 37.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1815/15290 [00:44<05:47, 38.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1820/15290 [00:44<05:42, 39.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1825/15290 [00:44<05:39, 39.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1830/15290 [00:44<05:30, 40.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1835/15290 [00:44<05:26, 41.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1840/15290 [00:44<05:34, 40.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1845/15290 [00:44<05:30, 40.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1850/15290 [00:44<05:36, 39.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1854/15290 [00:45<05:40, 39.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1859/15290 [00:45<05:34, 40.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1864/15290 [00:45<05:30, 40.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1869/15290 [00:45<05:25, 41.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1874/15290 [00:45<05:24, 41.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1879/15290 [00:45<05:18, 42.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1884/15290 [00:45<05:14, 42.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1889/15290 [00:45<05:14, 42.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1894/15290 [00:46<05:14, 42.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1899/15290 [00:46<05:19, 41.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1904/15290 [00:46<05:32, 40.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1909/15290 [00:46<05:32, 40.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1914/15290 [00:46<05:23, 41.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1919/15290 [00:46<05:15, 42.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1924/15290 [00:46<05:15, 42.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1929/15290 [00:46<05:13, 42.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1934/15290 [00:46<05:10, 43.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1939/15290 [00:47<05:09, 43.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1944/15290 [00:47<05:10, 42.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1949/15290 [00:47<05:15, 42.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1954/15290 [00:47<05:40, 39.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1959/15290 [00:47<05:33, 39.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1964/15290 [00:47<05:32, 40.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1969/15290 [00:47<05:31, 40.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1974/15290 [00:47<05:28, 40.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1979/15290 [00:48<05:25, 40.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1984/15290 [00:48<05:24, 41.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1989/15290 [00:48<05:26, 40.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1994/15290 [00:48<05:34, 39.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1998/15290 [00:48<05:41, 38.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2002/15290 [00:48<05:58, 37.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2006/15290 [00:48<05:53, 37.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2010/15290 [00:48<05:47, 38.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2015/15290 [00:49<05:39, 39.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2019/15290 [00:49<05:38, 39.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2024/15290 [00:49<05:32, 39.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2029/15290 [00:49<05:33, 39.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2033/15290 [00:49<05:35, 39.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2038/15290 [00:49<05:23, 40.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2043/15290 [00:49<05:19, 41.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2048/15290 [00:49<05:18, 41.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2053/15290 [00:49<05:19, 41.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2058/15290 [00:50<05:25, 40.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2063/15290 [00:50<05:47, 38.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2068/15290 [00:50<05:40, 38.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2073/15290 [00:50<05:34, 39.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2078/15290 [00:50<05:26, 40.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2083/15290 [00:50<05:23, 40.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2088/15290 [00:50<05:19, 41.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2093/15290 [00:50<05:17, 41.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2098/15290 [00:51<05:21, 41.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2103/15290 [00:51<05:16, 41.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2108/15290 [00:51<05:16, 41.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2113/15290 [00:51<05:15, 41.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2118/15290 [00:51<05:17, 41.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2123/15290 [00:51<05:15, 41.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2128/15290 [00:51<05:16, 41.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2133/15290 [00:51<05:11, 42.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2138/15290 [00:52<05:20, 41.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2143/15290 [00:52<05:27, 40.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2148/15290 [00:52<05:26, 40.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2153/15290 [00:52<05:27, 40.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2158/15290 [00:52<05:29, 39.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2162/15290 [00:52<05:35, 39.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2166/15290 [00:52<06:01, 36.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2170/15290 [00:52<05:55, 36.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2175/15290 [00:52<05:42, 38.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2179/15290 [00:53<05:40, 38.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2184/15290 [00:53<05:23, 40.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2189/15290 [00:53<05:16, 41.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2194/15290 [00:53<05:42, 38.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2198/15290 [00:53<05:38, 38.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2202/15290 [00:53<05:36, 38.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2207/15290 [00:53<05:28, 39.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2212/15290 [00:53<05:20, 40.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2217/15290 [00:54<05:19, 40.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2222/15290 [00:54<05:24, 40.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2227/15290 [00:54<05:57, 36.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2232/15290 [00:54<05:44, 37.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2237/15290 [00:54<05:29, 39.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2242/15290 [00:54<05:25, 40.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2247/15290 [00:54<05:37, 38.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2251/15290 [00:54<05:48, 37.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2255/15290 [00:55<05:44, 37.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2259/15290 [00:55<06:31, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2263/15290 [00:55<08:07, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2266/15290 [00:55<09:25, 23.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2270/15290 [00:55<08:13, 26.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2274/15290 [00:55<07:38, 28.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2279/15290 [00:55<06:47, 31.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2283/15290 [00:56<06:23, 33.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2288/15290 [00:56<05:50, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2293/15290 [00:56<05:31, 39.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2298/15290 [00:56<05:25, 39.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2303/15290 [00:56<05:23, 40.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2308/15290 [00:56<05:20, 40.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2313/15290 [00:56<05:12, 41.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2318/15290 [00:56<05:20, 40.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2323/15290 [00:56<05:21, 40.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2328/15290 [00:57<05:22, 40.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2333/15290 [00:57<05:28, 39.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2337/15290 [00:57<05:33, 38.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2341/15290 [00:57<05:40, 38.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2346/15290 [00:57<05:30, 39.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2350/15290 [00:57<05:28, 39.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2355/15290 [00:57<05:25, 39.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2360/15290 [00:57<05:21, 40.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2365/15290 [00:58<05:21, 40.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2370/15290 [00:58<05:18, 40.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2375/15290 [00:58<05:21, 40.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2380/15290 [00:58<05:28, 39.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2384/15290 [00:58<05:39, 38.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2388/15290 [00:58<05:34, 38.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2393/15290 [00:58<05:31, 38.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2398/15290 [00:58<05:26, 39.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2402/15290 [00:59<05:38, 38.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2406/15290 [00:59<05:46, 37.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2411/15290 [00:59<05:30, 38.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2416/15290 [00:59<05:22, 39.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2420/15290 [00:59<05:22, 39.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2424/15290 [00:59<05:24, 39.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2429/15290 [00:59<05:20, 40.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2434/15290 [00:59<05:13, 41.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2439/15290 [00:59<05:26, 39.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2443/15290 [01:00<05:33, 38.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2448/15290 [01:00<05:20, 40.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2453/15290 [01:00<05:13, 40.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2458/15290 [01:00<05:05, 42.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2463/15290 [01:00<05:02, 42.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2468/15290 [01:00<05:01, 42.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2473/15290 [01:00<05:03, 42.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2478/15290 [01:00<05:05, 41.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2483/15290 [01:00<05:03, 42.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2488/15290 [01:01<05:04, 42.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2493/15290 [01:01<05:02, 42.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2498/15290 [01:01<05:29, 38.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2502/15290 [01:01<05:30, 38.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2506/15290 [01:01<05:28, 38.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2511/15290 [01:01<05:25, 39.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2515/15290 [01:01<05:30, 38.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2520/15290 [01:01<05:20, 39.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2525/15290 [01:02<05:14, 40.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2530/15290 [01:02<05:09, 41.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2535/15290 [01:02<05:09, 41.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2540/15290 [01:02<05:16, 40.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2545/15290 [01:02<05:11, 40.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2550/15290 [01:02<05:09, 41.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2555/15290 [01:02<05:07, 41.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2560/15290 [01:02<05:18, 40.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2565/15290 [01:03<05:11, 40.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2570/15290 [01:03<05:11, 40.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2575/15290 [01:03<05:07, 41.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2580/15290 [01:03<05:07, 41.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2585/15290 [01:03<05:10, 40.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2590/15290 [01:03<05:10, 40.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2595/15290 [01:03<05:09, 41.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2600/15290 [01:03<05:23, 39.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2604/15290 [01:04<05:22, 39.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2608/15290 [01:04<05:22, 39.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2612/15290 [01:04<05:28, 38.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2617/15290 [01:04<05:19, 39.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2622/15290 [01:04<05:16, 40.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2627/15290 [01:04<05:20, 39.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2631/15290 [01:04<05:23, 39.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2636/15290 [01:04<05:17, 39.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2641/15290 [01:04<05:15, 40.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2646/15290 [01:05<05:19, 39.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2650/15290 [01:05<05:20, 39.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2654/15290 [01:05<05:24, 38.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2658/15290 [01:05<05:22, 39.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2663/15290 [01:05<05:20, 39.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2668/15290 [01:05<05:10, 40.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2673/15290 [01:05<05:04, 41.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2678/15290 [01:05<05:02, 41.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2683/15290 [01:05<05:17, 39.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2687/15290 [01:06<05:33, 37.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2692/15290 [01:06<05:23, 38.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2697/15290 [01:06<05:15, 39.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2702/15290 [01:06<05:11, 40.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2707/15290 [01:06<05:04, 41.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2712/15290 [01:06<05:08, 40.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2717/15290 [01:06<05:16, 39.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2721/15290 [01:06<05:28, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2725/15290 [01:07<05:27, 38.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2729/15290 [01:07<05:26, 38.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2733/15290 [01:07<05:25, 38.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2738/15290 [01:07<05:19, 39.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2743/15290 [01:07<05:14, 39.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2748/15290 [01:07<05:08, 40.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2753/15290 [01:07<05:00, 41.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2758/15290 [01:07<04:58, 42.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2763/15290 [01:07<04:58, 42.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2768/15290 [01:08<04:56, 42.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2773/15290 [01:08<04:54, 42.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2778/15290 [01:08<04:53, 42.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2783/15290 [01:08<04:55, 42.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2788/15290 [01:08<05:12, 39.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2793/15290 [01:08<05:14, 39.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2798/15290 [01:08<05:13, 39.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2803/15290 [01:08<05:16, 39.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2808/15290 [01:09<05:12, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2813/15290 [01:09<05:26, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2817/15290 [01:09<05:27, 38.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2821/15290 [01:09<05:25, 38.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2825/15290 [01:09<05:21, 38.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2830/15290 [01:09<05:18, 39.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2835/15290 [01:09<05:11, 39.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2840/15290 [01:09<05:06, 40.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2845/15290 [01:10<05:07, 40.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2850/15290 [01:10<05:06, 40.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2855/15290 [01:10<05:19, 38.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2859/15290 [01:10<05:20, 38.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2863/15290 [01:10<05:18, 38.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2867/15290 [01:10<05:19, 38.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2872/15290 [01:10<05:13, 39.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2876/15290 [01:10<05:15, 39.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2881/15290 [01:10<05:12, 39.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2886/15290 [01:11<05:12, 39.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2891/15290 [01:11<05:11, 39.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2895/15290 [01:11<05:20, 38.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2899/15290 [01:11<05:21, 38.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2903/15290 [01:11<05:28, 37.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2907/15290 [01:11<05:32, 37.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2911/15290 [01:11<05:29, 37.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2915/15290 [01:11<05:27, 37.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2920/15290 [01:11<05:14, 39.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2924/15290 [01:12<05:18, 38.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2929/15290 [01:12<05:13, 39.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2933/15290 [01:12<05:18, 38.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2938/15290 [01:12<05:10, 39.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2942/15290 [01:12<05:10, 39.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2946/15290 [01:12<05:23, 38.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2950/15290 [01:12<05:39, 36.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2954/15290 [01:12<05:30, 37.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2958/15290 [01:12<05:32, 37.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2963/15290 [01:13<05:17, 38.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2968/15290 [01:13<05:12, 39.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2972/15290 [01:13<05:19, 38.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2976/15290 [01:13<05:21, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2981/15290 [01:13<05:09, 39.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 2985/15290 [01:13<05:09, 39.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 2990/15290 [01:13<05:08, 39.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 2994/15290 [01:13<05:19, 38.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 2998/15290 [01:13<05:21, 38.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3002/15290 [01:14<05:21, 38.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3006/15290 [01:14<05:22, 38.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3010/15290 [01:14<05:21, 38.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3014/15290 [01:14<05:20, 38.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3018/15290 [01:14<05:27, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3023/15290 [01:14<05:17, 38.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3028/15290 [01:14<05:16, 38.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3033/15290 [01:14<05:03, 40.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3038/15290 [01:15<05:01, 40.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3043/15290 [01:15<04:58, 40.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3048/15290 [01:15<05:07, 39.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3052/15290 [01:15<05:13, 39.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3056/15290 [01:15<05:20, 38.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3061/15290 [01:15<05:13, 39.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3065/15290 [01:15<05:16, 38.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3070/15290 [01:15<05:12, 39.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3075/15290 [01:15<05:06, 39.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3079/15290 [01:16<05:08, 39.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3084/15290 [01:16<05:04, 40.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3089/15290 [01:16<05:04, 40.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3094/15290 [01:16<05:03, 40.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3099/15290 [01:16<05:00, 40.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3104/15290 [01:16<04:59, 40.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3109/15290 [01:16<04:55, 41.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3114/15290 [01:16<04:54, 41.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3119/15290 [01:17<05:03, 40.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3124/15290 [01:17<05:03, 40.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3129/15290 [01:17<05:06, 39.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3134/15290 [01:17<05:06, 39.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3138/15290 [01:17<05:08, 39.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3142/15290 [01:17<05:07, 39.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3146/15290 [01:17<05:07, 39.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3150/15290 [01:17<05:16, 38.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3155/15290 [01:17<05:06, 39.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3160/15290 [01:18<05:02, 40.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3165/15290 [01:18<05:03, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3169/15290 [01:18<05:04, 39.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3174/15290 [01:18<05:00, 40.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3179/15290 [01:18<04:52, 41.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3184/15290 [01:18<05:06, 39.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3189/15290 [01:18<05:00, 40.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3194/15290 [01:18<05:04, 39.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3198/15290 [01:19<05:03, 39.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3202/15290 [01:19<05:03, 39.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3206/15290 [01:19<05:09, 39.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3210/15290 [01:19<06:14, 32.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3214/15290 [01:19<05:59, 33.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3219/15290 [01:19<05:34, 36.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3224/15290 [01:19<05:22, 37.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3228/15290 [01:19<05:19, 37.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3233/15290 [01:19<05:05, 39.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3237/15290 [01:20<05:09, 38.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3241/15290 [01:20<05:14, 38.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3246/15290 [01:20<04:59, 40.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3251/15290 [01:20<04:54, 40.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3256/15290 [01:20<04:48, 41.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3261/15290 [01:20<04:51, 41.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3266/15290 [01:20<04:50, 41.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3271/15290 [01:20<04:52, 41.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3276/15290 [01:21<06:16, 31.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3281/15290 [01:21<05:48, 34.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3285/15290 [01:21<05:52, 34.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3289/15290 [01:21<06:36, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3294/15290 [01:21<06:03, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3298/15290 [01:21<05:47, 34.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3302/15290 [01:21<05:43, 34.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3306/15290 [01:22<05:41, 35.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3311/15290 [01:22<05:22, 37.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3315/15290 [01:22<05:33, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3319/15290 [01:22<05:30, 36.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3324/15290 [01:22<05:11, 38.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3329/15290 [01:22<05:02, 39.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3333/15290 [01:22<05:20, 37.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3337/15290 [01:22<05:17, 37.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3342/15290 [01:22<05:06, 39.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3347/15290 [01:23<05:10, 38.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3351/15290 [01:23<05:27, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3355/15290 [01:23<05:39, 35.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3359/15290 [01:23<05:33, 35.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3363/15290 [01:23<05:39, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3367/15290 [01:23<05:36, 35.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3371/15290 [01:23<05:35, 35.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3375/15290 [01:23<05:32, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3379/15290 [01:23<05:37, 35.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3383/15290 [01:24<05:29, 36.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3387/15290 [01:24<05:21, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3392/15290 [01:24<05:24, 36.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3396/15290 [01:24<05:21, 37.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3400/15290 [01:24<05:19, 37.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3404/15290 [01:24<05:15, 37.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3408/15290 [01:24<05:21, 36.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3412/15290 [01:24<05:19, 37.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3416/15290 [01:24<05:24, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3420/15290 [01:25<05:22, 36.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3424/15290 [01:25<05:20, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3428/15290 [01:25<05:23, 36.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3432/15290 [01:25<05:32, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3436/15290 [01:25<05:36, 35.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3440/15290 [01:25<05:31, 35.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3445/15290 [01:25<05:17, 37.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3449/15290 [01:25<05:17, 37.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3454/15290 [01:26<05:10, 38.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3458/15290 [01:26<05:09, 38.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3462/15290 [01:26<05:18, 37.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3466/15290 [01:26<05:32, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3470/15290 [01:26<05:45, 34.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3474/15290 [01:26<05:46, 34.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3478/15290 [01:26<05:56, 33.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3482/15290 [01:26<05:48, 33.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3486/15290 [01:26<05:57, 33.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3490/15290 [01:27<05:39, 34.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3494/15290 [01:27<05:46, 34.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3498/15290 [01:27<05:39, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3502/15290 [01:27<05:40, 34.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3506/15290 [01:27<05:53, 33.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3510/15290 [01:27<05:49, 33.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3514/15290 [01:27<05:34, 35.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3518/15290 [01:27<05:53, 33.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3522/15290 [01:28<05:50, 33.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3526/15290 [01:28<05:54, 33.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3530/15290 [01:28<05:37, 34.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3534/15290 [01:28<05:37, 34.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3538/15290 [01:28<05:42, 34.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3543/15290 [01:28<05:22, 36.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3547/15290 [01:28<05:26, 35.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3551/15290 [01:28<05:36, 34.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3556/15290 [01:28<05:14, 37.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3560/15290 [01:29<05:21, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3564/15290 [01:29<05:20, 36.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3568/15290 [01:29<05:33, 35.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3572/15290 [01:29<05:29, 35.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3576/15290 [01:29<05:37, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3580/15290 [01:29<05:44, 33.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3584/15290 [01:29<05:50, 33.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3588/15290 [01:29<05:41, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3592/15290 [01:30<05:52, 33.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3596/15290 [01:30<05:38, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3600/15290 [01:30<05:29, 35.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3604/15290 [01:30<06:01, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3608/15290 [01:30<05:59, 32.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3613/15290 [01:30<05:30, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3618/15290 [01:30<05:12, 37.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3622/15290 [01:30<05:10, 37.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3627/15290 [01:30<05:01, 38.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3631/15290 [01:31<05:46, 33.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3635/15290 [01:31<05:42, 34.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3639/15290 [01:31<06:00, 32.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3643/15290 [01:31<06:09, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3647/15290 [01:31<05:54, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3651/15290 [01:31<06:03, 32.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3655/15290 [01:31<05:43, 33.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3659/15290 [01:31<05:51, 33.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3663/15290 [01:32<06:02, 32.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3667/15290 [01:32<05:40, 34.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3671/15290 [01:32<05:31, 35.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3675/15290 [01:32<05:23, 35.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3680/15290 [01:32<05:10, 37.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3684/15290 [01:32<05:05, 38.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3689/15290 [01:32<04:56, 39.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3694/15290 [01:32<04:50, 39.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3698/15290 [01:33<04:57, 38.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3703/15290 [01:33<04:51, 39.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3708/15290 [01:33<04:48, 40.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3713/15290 [01:33<04:44, 40.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3718/15290 [01:33<04:42, 40.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3723/15290 [01:33<04:46, 40.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3728/15290 [01:33<04:53, 39.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3732/15290 [01:33<05:01, 38.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3736/15290 [01:33<05:00, 38.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3740/15290 [01:34<04:59, 38.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3745/15290 [01:34<04:49, 39.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3750/15290 [01:34<04:44, 40.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3755/15290 [01:34<04:46, 40.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3760/15290 [01:34<04:48, 39.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3764/15290 [01:34<05:00, 38.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3769/15290 [01:34<04:53, 39.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3773/15290 [01:34<04:54, 39.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3777/15290 [01:34<04:54, 39.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3782/15290 [01:35<04:49, 39.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3787/15290 [01:35<04:42, 40.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3792/15290 [01:35<04:37, 41.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3797/15290 [01:35<04:35, 41.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3802/15290 [01:35<04:38, 41.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3807/15290 [01:35<04:39, 41.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3812/15290 [01:35<04:50, 39.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3816/15290 [01:35<04:59, 38.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3820/15290 [01:36<05:10, 36.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3824/15290 [01:36<05:10, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3828/15290 [01:36<05:04, 37.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3832/15290 [01:36<05:03, 37.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3836/15290 [01:36<05:12, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3840/15290 [01:36<05:18, 35.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3844/15290 [01:36<05:16, 36.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3848/15290 [01:36<05:43, 33.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3852/15290 [01:37<05:57, 32.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3857/15290 [01:37<05:33, 34.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3861/15290 [01:37<05:34, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3865/15290 [01:37<05:27, 34.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3870/15290 [01:37<05:06, 37.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3875/15290 [01:37<04:56, 38.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3880/15290 [01:37<04:47, 39.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3885/15290 [01:37<04:42, 40.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3890/15290 [01:37<04:36, 41.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3895/15290 [01:38<04:33, 41.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3900/15290 [01:38<04:35, 41.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3905/15290 [01:38<04:36, 41.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3910/15290 [01:38<04:44, 40.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3915/15290 [01:38<04:44, 40.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3920/15290 [01:38<04:42, 40.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3925/15290 [01:38<04:43, 40.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3930/15290 [01:38<04:45, 39.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3934/15290 [01:39<04:52, 38.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3938/15290 [01:39<04:50, 39.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3942/15290 [01:39<05:29, 34.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3946/15290 [01:39<05:23, 35.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3951/15290 [01:39<05:05, 37.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3955/15290 [01:39<05:03, 37.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3959/15290 [01:39<05:04, 37.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3963/15290 [01:39<05:00, 37.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3967/15290 [01:39<04:57, 38.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3971/15290 [01:40<05:07, 36.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3975/15290 [01:40<05:00, 37.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3980/15290 [01:40<04:52, 38.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3984/15290 [01:40<05:10, 36.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3988/15290 [01:40<05:03, 37.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3992/15290 [01:40<04:58, 37.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3996/15290 [01:40<05:12, 36.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 4000/15290 [01:40<05:08, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 4004/15290 [01:40<05:04, 37.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 4008/15290 [01:41<05:22, 35.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 4012/15290 [01:41<05:38, 33.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4016/15290 [01:41<05:26, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4021/15290 [01:41<05:14, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4025/15290 [01:41<05:26, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4029/15290 [01:41<05:21, 35.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4034/15290 [01:41<05:09, 36.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4039/15290 [01:41<04:53, 38.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4043/15290 [01:42<04:51, 38.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4048/15290 [01:42<04:42, 39.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4052/15290 [01:42<04:54, 38.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4056/15290 [01:42<04:53, 38.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4060/15290 [01:42<04:57, 37.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4065/15290 [01:42<04:45, 39.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4070/15290 [01:42<04:41, 39.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4074/15290 [01:42<05:00, 37.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4078/15290 [01:43<05:21, 34.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4082/15290 [01:43<05:17, 35.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4086/15290 [01:43<05:11, 35.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4090/15290 [01:43<05:20, 34.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4094/15290 [01:43<05:19, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4098/15290 [01:43<05:26, 34.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4102/15290 [01:43<05:20, 34.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4106/15290 [01:43<05:21, 34.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4110/15290 [01:43<05:29, 33.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4115/15290 [01:44<05:10, 35.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4119/15290 [01:44<05:11, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4123/15290 [01:44<05:08, 36.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4127/15290 [01:44<05:05, 36.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4131/15290 [01:44<05:09, 36.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4135/15290 [01:44<05:06, 36.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4139/15290 [01:44<05:01, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4144/15290 [01:44<04:52, 38.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4148/15290 [01:44<04:57, 37.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4152/15290 [01:45<04:55, 37.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4156/15290 [01:45<04:56, 37.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4160/15290 [01:45<05:04, 36.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4165/15290 [01:45<04:52, 38.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4169/15290 [01:45<04:52, 37.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4173/15290 [01:45<04:51, 38.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4177/15290 [01:45<04:53, 37.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4181/15290 [01:45<04:51, 38.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4186/15290 [01:45<04:41, 39.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4190/15290 [01:46<04:41, 39.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4194/15290 [01:46<04:47, 38.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4198/15290 [01:46<05:00, 36.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4202/15290 [01:46<04:56, 37.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4206/15290 [01:46<05:08, 35.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4210/15290 [01:46<05:06, 36.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4214/15290 [01:46<05:25, 34.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4218/15290 [01:46<05:39, 32.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4222/15290 [01:46<05:33, 33.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4226/15290 [01:47<05:26, 33.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4230/15290 [01:47<05:13, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4235/15290 [01:47<04:57, 37.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4240/15290 [01:47<04:49, 38.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4244/15290 [01:47<04:50, 38.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4248/15290 [01:47<04:50, 38.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4253/15290 [01:47<04:41, 39.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4257/15290 [01:47<04:42, 38.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4261/15290 [01:47<04:41, 39.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4265/15290 [01:48<04:41, 39.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4270/15290 [01:48<04:34, 40.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4275/15290 [01:48<04:46, 38.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4279/15290 [01:48<04:59, 36.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4283/15290 [01:48<04:52, 37.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4287/15290 [01:48<04:47, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4291/15290 [01:48<04:45, 38.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4296/15290 [01:48<04:38, 39.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4300/15290 [01:48<04:49, 38.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4304/15290 [01:49<04:46, 38.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4308/15290 [01:49<04:42, 38.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4312/15290 [01:49<04:50, 37.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4316/15290 [01:49<05:02, 36.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4320/15290 [01:49<04:57, 36.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4324/15290 [01:49<05:00, 36.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4328/15290 [01:49<05:08, 35.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4332/15290 [01:49<04:58, 36.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4336/15290 [01:49<04:54, 37.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4340/15290 [01:50<05:08, 35.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4344/15290 [01:50<04:58, 36.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4348/15290 [01:50<04:52, 37.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4353/15290 [01:50<04:42, 38.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4357/15290 [01:50<04:53, 37.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4361/15290 [01:50<05:05, 35.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4365/15290 [01:50<04:58, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4370/15290 [01:50<04:46, 38.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4374/15290 [01:50<04:43, 38.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4379/15290 [01:51<04:37, 39.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4384/15290 [01:51<04:33, 39.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4388/15290 [01:51<04:34, 39.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4392/15290 [01:51<04:40, 38.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4396/15290 [01:51<04:50, 37.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4400/15290 [01:51<04:49, 37.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4404/15290 [01:51<04:57, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4408/15290 [01:51<04:52, 37.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4412/15290 [01:51<04:58, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4416/15290 [01:52<05:06, 35.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4420/15290 [01:52<05:23, 33.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4424/15290 [01:52<05:15, 34.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4428/15290 [01:52<05:05, 35.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4433/15290 [01:52<04:50, 37.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4438/15290 [01:52<04:40, 38.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4442/15290 [01:52<05:05, 35.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4446/15290 [01:52<05:13, 34.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4450/15290 [01:53<05:20, 33.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4454/15290 [01:53<05:20, 33.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4459/15290 [01:53<05:05, 35.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4463/15290 [01:53<05:02, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4468/15290 [01:53<04:50, 37.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4473/15290 [01:53<04:40, 38.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4478/15290 [01:53<04:34, 39.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4483/15290 [01:53<04:29, 40.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4488/15290 [01:54<04:24, 40.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4493/15290 [01:54<04:31, 39.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4497/15290 [01:54<04:34, 39.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4501/15290 [01:54<04:35, 39.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4505/15290 [01:54<04:40, 38.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4509/15290 [01:54<04:39, 38.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4513/15290 [01:54<04:37, 38.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4518/15290 [01:54<04:33, 39.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4522/15290 [01:54<04:36, 39.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4527/15290 [01:55<04:27, 40.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4532/15290 [01:55<04:32, 39.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4536/15290 [01:55<04:36, 38.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4540/15290 [01:55<04:41, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4544/15290 [01:55<05:11, 34.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4548/15290 [01:55<05:12, 34.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4552/15290 [01:55<05:10, 34.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4556/15290 [01:55<05:14, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4560/15290 [01:56<05:15, 34.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4564/15290 [01:56<05:13, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4568/15290 [01:56<05:09, 34.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4572/15290 [01:56<05:05, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4576/15290 [01:56<04:54, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4580/15290 [01:56<05:06, 34.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4585/15290 [01:56<04:50, 36.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4589/15290 [01:56<04:46, 37.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4594/15290 [01:56<04:37, 38.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4598/15290 [01:57<04:39, 38.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4603/15290 [01:57<04:33, 39.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4607/15290 [01:57<04:47, 37.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4611/15290 [01:57<04:52, 36.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4615/15290 [01:57<04:55, 36.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4619/15290 [01:57<04:49, 36.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4623/15290 [01:57<04:44, 37.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4628/15290 [01:57<04:35, 38.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4632/15290 [01:57<04:38, 38.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4637/15290 [01:58<04:31, 39.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4641/15290 [01:58<04:33, 38.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4645/15290 [01:58<04:36, 38.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4649/15290 [01:58<04:44, 37.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4653/15290 [01:58<04:39, 38.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4657/15290 [01:58<04:39, 38.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4661/15290 [01:58<04:41, 37.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4665/15290 [01:58<04:45, 37.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4669/15290 [01:58<04:47, 36.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4673/15290 [01:59<04:43, 37.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4677/15290 [01:59<04:38, 38.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4682/15290 [01:59<04:32, 38.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4686/15290 [01:59<04:32, 38.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4690/15290 [01:59<04:35, 38.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4694/15290 [01:59<04:35, 38.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4698/15290 [01:59<04:39, 37.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4702/15290 [01:59<04:38, 37.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4706/15290 [01:59<04:41, 37.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4710/15290 [02:00<05:04, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4714/15290 [02:00<05:06, 34.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4718/15290 [02:00<04:59, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4722/15290 [02:00<04:51, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4726/15290 [02:00<04:48, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4730/15290 [02:00<04:46, 36.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4734/15290 [02:00<04:45, 37.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4738/15290 [02:00<04:39, 37.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4743/15290 [02:00<04:32, 38.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4747/15290 [02:00<04:30, 38.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4751/15290 [02:01<04:29, 39.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4755/15290 [02:01<04:28, 39.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4759/15290 [02:01<04:34, 38.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4763/15290 [02:01<04:43, 37.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4767/15290 [02:01<04:42, 37.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4771/15290 [02:01<04:57, 35.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4775/15290 [02:01<05:02, 34.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4779/15290 [02:01<05:13, 33.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4783/15290 [02:02<05:09, 33.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4787/15290 [02:02<04:55, 35.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4792/15290 [02:02<04:40, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4796/15290 [02:02<04:43, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4801/15290 [02:02<04:34, 38.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4805/15290 [02:02<04:32, 38.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4809/15290 [02:02<04:37, 37.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4813/15290 [02:02<04:41, 37.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4817/15290 [02:02<04:46, 36.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4822/15290 [02:03<04:32, 38.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4827/15290 [02:03<04:27, 39.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4831/15290 [02:03<04:28, 38.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4835/15290 [02:03<04:32, 38.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4839/15290 [02:03<04:37, 37.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4843/15290 [02:03<04:39, 37.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4847/15290 [02:03<04:41, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4851/15290 [02:03<04:53, 35.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4855/15290 [02:03<05:05, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4859/15290 [02:04<04:53, 35.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4863/15290 [02:04<04:51, 35.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4868/15290 [02:04<04:34, 38.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4873/15290 [02:04<04:27, 38.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4877/15290 [02:04<04:26, 39.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4881/15290 [02:04<04:27, 38.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4886/15290 [02:04<04:27, 38.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4890/15290 [02:04<04:30, 38.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4894/15290 [02:04<04:29, 38.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4898/15290 [02:05<05:00, 34.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4902/15290 [02:05<04:54, 35.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4907/15290 [02:05<04:42, 36.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4911/15290 [02:05<04:40, 37.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4916/15290 [02:05<04:32, 38.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4920/15290 [02:05<04:39, 37.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4924/15290 [02:05<04:37, 37.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4928/15290 [02:05<04:37, 37.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4932/15290 [02:05<04:41, 36.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4936/15290 [02:06<04:50, 35.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4940/15290 [02:06<04:44, 36.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4944/15290 [02:06<04:38, 37.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4949/15290 [02:06<04:32, 37.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4953/15290 [02:06<04:32, 37.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4957/15290 [02:06<04:30, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4962/15290 [02:06<04:22, 39.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4967/15290 [02:06<04:16, 40.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4972/15290 [02:07<04:17, 40.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4977/15290 [02:07<04:27, 38.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4981/15290 [02:07<04:28, 38.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4985/15290 [02:07<04:34, 37.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4989/15290 [02:07<04:37, 37.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4993/15290 [02:07<04:53, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4997/15290 [02:07<05:03, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5001/15290 [02:07<04:57, 34.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5005/15290 [02:07<04:50, 35.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5009/15290 [02:08<04:43, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5013/15290 [02:08<04:42, 36.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5017/15290 [02:08<04:40, 36.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5021/15290 [02:08<04:53, 35.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5025/15290 [02:08<05:12, 32.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5030/15290 [02:08<04:51, 35.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5035/15290 [02:08<04:38, 36.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5039/15290 [02:08<04:53, 34.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5043/15290 [02:09<04:49, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5047/15290 [02:09<04:42, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5052/15290 [02:09<04:34, 37.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5056/15290 [02:09<04:53, 34.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5061/15290 [02:09<04:39, 36.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5065/15290 [02:09<04:38, 36.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5069/15290 [02:09<04:47, 35.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5073/15290 [02:09<04:44, 35.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5078/15290 [02:09<04:33, 37.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5082/15290 [02:10<04:31, 37.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5087/15290 [02:10<04:24, 38.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5092/15290 [02:10<04:19, 39.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5096/15290 [02:10<04:17, 39.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5100/15290 [02:10<04:24, 38.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5105/15290 [02:10<04:19, 39.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5109/15290 [02:10<04:27, 38.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5113/15290 [02:10<04:52, 34.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5117/15290 [02:11<04:58, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5121/15290 [02:11<04:49, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5125/15290 [02:11<04:45, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5129/15290 [02:11<05:02, 33.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5133/15290 [02:11<05:09, 32.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5138/15290 [02:11<04:47, 35.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5142/15290 [02:11<04:40, 36.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5147/15290 [02:11<04:28, 37.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5151/15290 [02:11<04:25, 38.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5156/15290 [02:12<04:19, 39.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5160/15290 [02:12<04:21, 38.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5164/15290 [02:12<04:22, 38.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5168/15290 [02:12<04:47, 35.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5172/15290 [02:12<04:49, 34.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5176/15290 [02:12<04:44, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5180/15290 [02:12<04:34, 36.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5184/15290 [02:12<04:28, 37.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5189/15290 [02:12<04:20, 38.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5193/15290 [02:13<04:28, 37.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5197/15290 [02:13<04:26, 37.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5201/15290 [02:13<04:25, 37.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5206/15290 [02:13<04:19, 38.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5211/15290 [02:13<04:15, 39.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5216/15290 [02:13<04:12, 39.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5221/15290 [02:13<04:11, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5225/15290 [02:13<04:11, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5229/15290 [02:13<04:12, 39.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5234/15290 [02:14<04:10, 40.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5239/15290 [02:14<04:43, 35.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5243/15290 [02:14<04:54, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5247/15290 [02:14<04:52, 34.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5251/15290 [02:14<04:45, 35.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5255/15290 [02:14<04:39, 35.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5259/15290 [02:14<04:42, 35.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5263/15290 [02:14<04:45, 35.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5267/15290 [02:15<04:46, 35.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5271/15290 [02:15<04:43, 35.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5275/15290 [02:15<04:46, 34.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5279/15290 [02:15<04:46, 35.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5283/15290 [02:15<04:46, 34.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5287/15290 [02:15<04:42, 35.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5291/15290 [02:15<04:57, 33.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5295/15290 [02:15<05:16, 31.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5299/15290 [02:16<04:57, 33.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5303/15290 [02:16<04:44, 35.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5307/15290 [02:16<04:37, 35.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5312/15290 [02:16<04:26, 37.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5316/15290 [02:16<04:30, 36.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5320/15290 [02:16<04:46, 34.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5324/15290 [02:16<04:44, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5328/15290 [02:16<04:33, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5332/15290 [02:16<04:35, 36.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5336/15290 [02:17<04:50, 34.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5340/15290 [02:17<04:45, 34.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5344/15290 [02:17<04:40, 35.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5349/15290 [02:17<04:27, 37.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5353/15290 [02:17<04:21, 37.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5357/15290 [02:17<04:55, 33.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5361/15290 [02:17<05:02, 32.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5365/15290 [02:17<04:51, 34.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5369/15290 [02:18<04:54, 33.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5373/15290 [02:18<05:02, 32.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5377/15290 [02:18<04:55, 33.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5381/15290 [02:18<04:43, 34.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5385/15290 [02:18<04:36, 35.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5389/15290 [02:18<04:33, 36.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5393/15290 [02:18<04:30, 36.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5397/15290 [02:18<04:45, 34.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5401/15290 [02:18<05:15, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5405/15290 [02:19<04:59, 33.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5409/15290 [02:19<04:49, 34.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5413/15290 [02:19<04:45, 34.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5418/15290 [02:19<04:29, 36.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5422/15290 [02:19<04:26, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5426/15290 [02:19<04:29, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5430/15290 [02:19<04:31, 36.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5434/15290 [02:19<04:39, 35.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5438/15290 [02:20<05:00, 32.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5442/15290 [02:20<04:55, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5446/15290 [02:20<04:47, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5450/15290 [02:20<04:59, 32.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5454/15290 [02:20<05:04, 32.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5458/15290 [02:20<04:53, 33.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5463/15290 [02:20<04:35, 35.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5468/15290 [02:20<04:24, 37.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5472/15290 [02:20<04:43, 34.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5476/15290 [02:21<04:43, 34.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5480/15290 [02:21<04:42, 34.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5484/15290 [02:21<04:34, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5488/15290 [02:21<04:28, 36.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5492/15290 [02:21<04:35, 35.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5496/15290 [02:21<04:33, 35.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5500/15290 [02:21<04:30, 36.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5504/15290 [02:21<04:23, 37.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5508/15290 [02:21<04:19, 37.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5512/15290 [02:22<04:16, 38.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5516/15290 [02:22<04:15, 38.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5520/15290 [02:22<04:12, 38.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5524/15290 [02:22<04:23, 37.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5528/15290 [02:22<04:29, 36.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5532/15290 [02:22<04:36, 35.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5536/15290 [02:22<04:36, 35.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5540/15290 [02:22<04:35, 35.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5544/15290 [02:22<04:42, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5548/15290 [02:23<04:39, 34.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5552/15290 [02:23<04:40, 34.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5556/15290 [02:23<04:34, 35.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5560/15290 [02:23<04:33, 35.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5564/15290 [02:23<04:32, 35.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5568/15290 [02:23<04:37, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5572/15290 [02:23<04:29, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5576/15290 [02:23<04:29, 36.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5580/15290 [02:23<04:41, 34.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5584/15290 [02:24<04:38, 34.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5588/15290 [02:24<04:32, 35.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5592/15290 [02:24<06:37, 24.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5595/15290 [02:24<07:03, 22.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5598/15290 [02:24<07:28, 21.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5601/15290 [02:24<07:03, 22.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5604/15290 [02:25<06:52, 23.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5609/15290 [02:25<05:45, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5613/15290 [02:25<05:13, 30.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5618/15290 [02:25<04:47, 33.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5622/15290 [02:25<04:47, 33.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5626/15290 [02:25<04:43, 34.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5630/15290 [02:25<04:33, 35.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5634/15290 [02:25<04:31, 35.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5638/15290 [02:25<04:26, 36.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5642/15290 [02:26<04:20, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5646/15290 [02:26<04:20, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5650/15290 [02:26<04:23, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5654/15290 [02:26<04:19, 37.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5658/15290 [02:26<04:18, 37.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5662/15290 [02:26<04:31, 35.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5666/15290 [02:26<04:34, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5670/15290 [02:26<04:25, 36.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5674/15290 [02:26<04:30, 35.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5678/15290 [02:27<04:24, 36.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5682/15290 [02:27<04:25, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5686/15290 [02:27<04:20, 36.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5690/15290 [02:27<04:27, 35.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5694/15290 [02:27<04:27, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5698/15290 [02:27<04:24, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5702/15290 [02:27<04:18, 37.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5707/15290 [02:27<04:07, 38.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5712/15290 [02:27<04:02, 39.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5716/15290 [02:28<04:03, 39.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5720/15290 [02:28<04:06, 38.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5725/15290 [02:28<04:02, 39.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5729/15290 [02:28<04:05, 38.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5733/15290 [02:28<04:11, 38.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5737/15290 [02:28<04:11, 38.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5741/15290 [02:28<04:08, 38.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5745/15290 [02:28<04:10, 38.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5749/15290 [02:28<04:07, 38.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5753/15290 [02:29<04:47, 33.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5757/15290 [02:29<04:54, 32.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5761/15290 [02:29<04:58, 31.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5765/15290 [02:29<05:52, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5769/15290 [02:29<05:27, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5773/15290 [02:29<05:01, 31.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5777/15290 [02:29<04:46, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5782/15290 [02:29<04:30, 35.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5786/15290 [02:30<04:26, 35.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5791/15290 [02:30<04:18, 36.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5795/15290 [02:30<04:47, 33.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5799/15290 [02:30<04:43, 33.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5803/15290 [02:30<04:32, 34.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5807/15290 [02:30<04:47, 32.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5811/15290 [02:30<04:46, 33.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5815/15290 [02:30<04:37, 34.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5819/15290 [02:31<04:28, 35.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5823/15290 [02:31<04:26, 35.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5827/15290 [02:31<04:34, 34.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5831/15290 [02:31<04:38, 33.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5835/15290 [02:31<04:28, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5839/15290 [02:31<04:25, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5843/15290 [02:31<04:35, 34.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5847/15290 [02:31<04:57, 31.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5851/15290 [02:32<04:52, 32.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5856/15290 [02:32<04:32, 34.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5860/15290 [02:32<04:24, 35.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5864/15290 [02:32<04:19, 36.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5868/15290 [02:32<04:17, 36.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5872/15290 [02:32<04:16, 36.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5876/15290 [02:32<04:15, 36.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5880/15290 [02:32<04:09, 37.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5884/15290 [02:32<04:08, 37.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5888/15290 [02:33<04:25, 35.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5892/15290 [02:33<04:40, 33.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5896/15290 [02:33<04:28, 34.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5900/15290 [02:33<04:24, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5904/15290 [02:33<04:46, 32.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5908/15290 [02:33<04:41, 33.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5912/15290 [02:33<04:30, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5916/15290 [02:33<04:36, 33.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5920/15290 [02:33<04:28, 34.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5924/15290 [02:34<04:25, 35.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5928/15290 [02:34<04:16, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5932/15290 [02:34<04:13, 36.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5936/15290 [02:34<04:11, 37.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5940/15290 [02:34<04:06, 37.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5945/15290 [02:34<04:04, 38.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5949/15290 [02:34<04:12, 36.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5953/15290 [02:34<05:03, 30.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5957/15290 [02:35<04:53, 31.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5961/15290 [02:35<05:07, 30.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5965/15290 [02:35<05:14, 29.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5969/15290 [02:35<04:56, 31.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5973/15290 [02:35<04:40, 33.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5977/15290 [02:35<05:04, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5981/15290 [02:35<04:54, 31.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5985/15290 [02:35<04:38, 33.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5989/15290 [02:35<04:26, 34.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5993/15290 [02:36<04:17, 36.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5997/15290 [02:36<04:13, 36.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6001/15290 [02:36<04:10, 37.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6005/15290 [02:36<04:11, 36.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6009/15290 [02:36<04:15, 36.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6013/15290 [02:36<04:09, 37.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6018/15290 [02:36<04:02, 38.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6022/15290 [02:36<04:23, 35.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6026/15290 [02:37<04:29, 34.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6030/15290 [02:37<04:19, 35.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6034/15290 [02:37<04:17, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6038/15290 [02:37<04:43, 32.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6042/15290 [02:37<04:30, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6046/15290 [02:37<04:39, 33.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6050/15290 [02:37<04:48, 32.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6054/15290 [02:37<04:33, 33.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6059/15290 [02:37<04:18, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6063/15290 [02:38<04:54, 31.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6067/15290 [02:38<04:56, 31.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6071/15290 [02:38<04:39, 33.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6075/15290 [02:38<04:41, 32.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6079/15290 [02:38<04:48, 31.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6084/15290 [02:38<04:28, 34.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6088/15290 [02:38<04:41, 32.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6092/15290 [02:39<04:42, 32.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6096/15290 [02:39<04:27, 34.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6100/15290 [02:39<04:21, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6104/15290 [02:39<04:42, 32.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6108/15290 [02:39<04:44, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6112/15290 [02:39<04:30, 33.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6117/15290 [02:39<04:15, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6121/15290 [02:39<04:50, 31.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6125/15290 [02:40<04:56, 30.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6129/15290 [02:40<04:37, 32.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6133/15290 [02:40<04:24, 34.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6137/15290 [02:40<04:15, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6141/15290 [02:40<04:12, 36.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6145/15290 [02:40<04:24, 34.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6149/15290 [02:40<04:31, 33.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6153/15290 [02:40<04:23, 34.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6157/15290 [02:40<04:13, 36.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6162/15290 [02:41<04:01, 37.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6166/15290 [02:41<04:07, 36.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6170/15290 [02:41<04:10, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6174/15290 [02:41<04:07, 36.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6178/15290 [02:41<04:09, 36.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6182/15290 [02:41<04:09, 36.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6186/15290 [02:41<04:12, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6190/15290 [02:41<04:07, 36.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6194/15290 [02:41<04:05, 37.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6198/15290 [02:42<03:59, 37.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6202/15290 [02:42<05:04, 29.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6206/15290 [02:42<04:58, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6210/15290 [02:42<04:56, 30.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6214/15290 [02:42<04:46, 31.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6218/15290 [02:42<04:53, 30.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6222/15290 [02:42<04:48, 31.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6226/15290 [02:42<04:51, 31.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6230/15290 [02:43<04:56, 30.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6234/15290 [02:43<04:39, 32.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6238/15290 [02:43<04:27, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6242/15290 [02:43<04:18, 35.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6246/15290 [02:43<04:10, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6250/15290 [02:43<04:03, 37.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6254/15290 [02:43<04:03, 37.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6258/15290 [02:43<04:00, 37.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6262/15290 [02:43<04:03, 37.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6266/15290 [02:44<04:44, 31.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6270/15290 [02:44<04:39, 32.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6274/15290 [02:44<04:47, 31.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6278/15290 [02:44<04:53, 30.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6282/15290 [02:44<04:39, 32.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6286/15290 [02:44<04:25, 33.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6290/15290 [02:44<04:27, 33.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6294/15290 [02:44<04:43, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6298/15290 [02:45<04:42, 31.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6302/15290 [02:45<04:27, 33.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6306/15290 [02:45<04:23, 34.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6310/15290 [02:45<04:13, 35.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6314/15290 [02:45<04:07, 36.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6319/15290 [02:45<03:57, 37.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6323/15290 [02:45<03:57, 37.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6327/15290 [02:45<04:21, 34.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6331/15290 [02:46<04:25, 33.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6335/15290 [02:46<04:30, 33.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6339/15290 [02:46<04:58, 29.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6343/15290 [02:46<04:40, 31.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6347/15290 [02:46<04:29, 33.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6351/15290 [02:46<04:26, 33.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6355/15290 [02:46<04:20, 34.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6359/15290 [02:46<04:23, 33.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6363/15290 [02:46<04:22, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6367/15290 [02:47<04:17, 34.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6371/15290 [02:47<04:14, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6375/15290 [02:47<04:19, 34.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6379/15290 [02:47<04:14, 35.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6383/15290 [02:47<04:09, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6387/15290 [02:47<04:13, 35.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6391/15290 [02:47<04:09, 35.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6395/15290 [02:47<04:13, 35.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6399/15290 [02:48<04:10, 35.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6403/15290 [02:48<04:09, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6407/15290 [02:48<04:04, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6411/15290 [02:48<04:02, 36.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6415/15290 [02:48<04:03, 36.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6419/15290 [02:48<04:03, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6423/15290 [02:48<04:07, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6427/15290 [02:48<04:24, 33.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6431/15290 [02:48<04:29, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6435/15290 [02:49<04:27, 33.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6439/15290 [02:49<04:20, 33.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6443/15290 [02:49<04:17, 34.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6447/15290 [02:49<04:31, 32.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6451/15290 [02:49<04:40, 31.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6455/15290 [02:49<04:47, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6459/15290 [02:49<04:49, 30.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6463/15290 [02:49<04:39, 31.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6468/15290 [02:50<04:09, 35.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6473/15290 [02:50<03:57, 37.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6477/15290 [02:50<04:14, 34.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6481/15290 [02:50<04:08, 35.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6486/15290 [02:50<03:52, 37.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6490/15290 [02:50<04:00, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6494/15290 [02:50<04:10, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6498/15290 [02:50<04:13, 34.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6502/15290 [02:50<04:10, 35.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6506/15290 [02:51<04:10, 35.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6510/15290 [02:51<04:10, 35.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6514/15290 [02:51<04:02, 36.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6518/15290 [02:51<03:56, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6522/15290 [02:51<04:03, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6526/15290 [02:51<03:56, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6530/15290 [02:51<03:52, 37.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6534/15290 [02:51<03:53, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6538/15290 [02:51<03:59, 36.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6542/15290 [02:52<03:56, 37.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6546/15290 [02:52<03:57, 36.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6550/15290 [02:52<04:05, 35.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6554/15290 [02:52<04:04, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6558/15290 [02:52<04:00, 36.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6562/15290 [02:52<04:07, 35.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6566/15290 [02:52<04:38, 31.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6570/15290 [02:52<04:26, 32.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6574/15290 [02:53<04:14, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6578/15290 [02:53<04:07, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6582/15290 [02:53<04:01, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6586/15290 [02:53<03:57, 36.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6590/15290 [02:53<03:53, 37.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6595/15290 [02:53<03:46, 38.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6599/15290 [02:53<03:46, 38.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6603/15290 [02:53<03:43, 38.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6607/15290 [02:53<03:42, 39.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6611/15290 [02:53<03:44, 38.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6615/15290 [02:54<03:45, 38.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6619/15290 [02:54<03:47, 38.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6623/15290 [02:54<03:45, 38.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6627/15290 [02:54<03:44, 38.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6631/15290 [02:54<03:42, 39.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6635/15290 [02:54<03:41, 39.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6639/15290 [02:54<03:39, 39.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6643/15290 [02:54<03:47, 38.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6647/15290 [02:54<03:43, 38.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6651/15290 [02:55<03:47, 38.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6655/15290 [02:55<03:45, 38.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6659/15290 [02:55<04:59, 28.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6663/15290 [02:55<04:41, 30.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6667/15290 [02:55<04:28, 32.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6671/15290 [02:55<04:15, 33.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6675/15290 [02:55<04:06, 34.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6679/15290 [02:55<04:01, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6683/15290 [02:55<03:54, 36.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6687/15290 [02:56<03:58, 36.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6691/15290 [02:56<03:55, 36.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6695/15290 [02:56<03:51, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6699/15290 [02:56<03:48, 37.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6703/15290 [02:56<03:46, 37.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6707/15290 [02:56<03:42, 38.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6711/15290 [02:56<03:45, 38.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6715/15290 [02:56<03:50, 37.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6719/15290 [02:56<03:46, 37.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6723/15290 [02:57<03:44, 38.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6728/15290 [02:57<03:39, 38.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6732/15290 [02:57<04:03, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6736/15290 [02:57<04:29, 31.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6740/15290 [02:57<04:20, 32.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6745/15290 [02:57<04:05, 34.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6749/15290 [02:57<03:56, 36.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6753/15290 [02:57<03:51, 36.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6757/15290 [02:58<03:58, 35.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6761/15290 [02:58<04:02, 35.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6765/15290 [02:58<04:08, 34.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6769/15290 [02:58<04:06, 34.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6773/15290 [02:58<03:58, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6777/15290 [02:58<03:53, 36.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6781/15290 [02:58<03:48, 37.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6785/15290 [02:58<03:45, 37.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6789/15290 [02:58<03:49, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6793/15290 [02:59<03:49, 37.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6797/15290 [02:59<03:44, 37.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6801/15290 [02:59<03:45, 37.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6805/15290 [02:59<03:43, 38.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6809/15290 [02:59<03:43, 37.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6814/15290 [02:59<03:37, 38.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6818/15290 [02:59<03:37, 38.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6822/15290 [02:59<03:36, 39.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6826/15290 [02:59<03:36, 39.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6830/15290 [02:59<03:40, 38.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6834/15290 [03:00<03:55, 35.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6838/15290 [03:00<03:52, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6842/15290 [03:00<03:48, 37.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6846/15290 [03:00<03:44, 37.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6850/15290 [03:00<03:45, 37.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6854/15290 [03:00<03:47, 37.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6858/15290 [03:00<03:52, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6862/15290 [03:00<03:50, 36.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6866/15290 [03:00<03:58, 35.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6870/15290 [03:01<03:54, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6874/15290 [03:01<03:53, 36.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6878/15290 [03:01<03:50, 36.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6882/15290 [03:01<03:46, 37.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6886/15290 [03:01<03:43, 37.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6890/15290 [03:01<03:42, 37.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6894/15290 [03:01<03:40, 38.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6898/15290 [03:01<03:52, 36.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6902/15290 [03:01<03:51, 36.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6906/15290 [03:02<03:53, 35.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6910/15290 [03:02<03:52, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6914/15290 [03:02<04:48, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6918/15290 [03:02<05:18, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6922/15290 [03:02<04:49, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6926/15290 [03:02<04:32, 30.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6930/15290 [03:02<04:51, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6934/15290 [03:03<04:43, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6938/15290 [03:03<04:28, 31.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6942/15290 [03:03<04:15, 32.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6946/15290 [03:03<04:07, 33.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6950/15290 [03:03<04:01, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6954/15290 [03:03<04:03, 34.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6958/15290 [03:03<04:05, 33.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6962/15290 [03:03<04:00, 34.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6966/15290 [03:04<04:47, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6970/15290 [03:04<04:46, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6974/15290 [03:04<04:31, 30.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6978/15290 [03:04<04:13, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6982/15290 [03:04<04:32, 30.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6986/15290 [03:04<04:26, 31.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6990/15290 [03:04<04:17, 32.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6994/15290 [03:04<04:08, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6998/15290 [03:04<04:05, 33.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7002/15290 [03:05<04:05, 33.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7006/15290 [03:05<04:07, 33.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7010/15290 [03:05<04:07, 33.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7014/15290 [03:05<04:24, 31.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7018/15290 [03:05<04:38, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7022/15290 [03:05<04:25, 31.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7026/15290 [03:05<04:13, 32.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7030/15290 [03:05<04:07, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7034/15290 [03:06<04:14, 32.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7038/15290 [03:06<04:09, 33.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7042/15290 [03:06<04:02, 34.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7046/15290 [03:06<03:54, 35.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7050/15290 [03:06<03:53, 35.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7054/15290 [03:06<04:44, 28.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7058/15290 [03:06<04:28, 30.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7062/15290 [03:06<04:16, 32.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7066/15290 [03:07<04:04, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7070/15290 [03:07<04:02, 33.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7074/15290 [03:07<04:01, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7078/15290 [03:07<04:01, 33.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7082/15290 [03:07<03:56, 34.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7086/15290 [03:07<03:55, 34.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7090/15290 [03:07<03:53, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7094/15290 [03:07<03:46, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7098/15290 [03:07<03:45, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7102/15290 [03:08<03:39, 37.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7106/15290 [03:08<03:42, 36.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7110/15290 [03:08<03:52, 35.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7114/15290 [03:08<03:49, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7118/15290 [03:08<03:53, 34.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7122/15290 [03:08<04:00, 34.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7126/15290 [03:08<03:51, 35.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7130/15290 [03:08<03:48, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7134/15290 [03:08<03:42, 36.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7138/15290 [03:09<03:37, 37.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7142/15290 [03:09<03:35, 37.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7146/15290 [03:09<03:36, 37.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7150/15290 [03:09<03:36, 37.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7154/15290 [03:09<03:36, 37.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7158/15290 [03:09<03:34, 37.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7162/15290 [03:09<03:34, 37.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7166/15290 [03:09<04:23, 30.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7170/15290 [03:10<04:51, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7174/15290 [03:10<04:28, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7178/15290 [03:10<04:10, 32.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7182/15290 [03:10<04:00, 33.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7187/15290 [03:10<03:45, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7191/15290 [03:10<03:44, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7195/15290 [03:10<03:53, 34.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7199/15290 [03:10<03:47, 35.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7203/15290 [03:10<03:45, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7207/15290 [03:11<03:38, 36.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7211/15290 [03:11<03:40, 36.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7215/15290 [03:11<03:41, 36.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7219/15290 [03:11<03:43, 36.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7223/15290 [03:11<03:42, 36.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7227/15290 [03:11<03:42, 36.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7231/15290 [03:11<03:41, 36.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7235/15290 [03:11<03:36, 37.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7239/15290 [03:11<03:31, 38.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7243/15290 [03:12<03:32, 37.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7247/15290 [03:12<03:33, 37.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7251/15290 [03:12<03:39, 36.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7255/15290 [03:12<03:41, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7259/15290 [03:12<03:49, 34.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7263/15290 [03:12<03:48, 35.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7267/15290 [03:12<03:43, 35.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7271/15290 [03:12<03:39, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7275/15290 [03:12<03:37, 36.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7279/15290 [03:13<03:38, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7283/15290 [03:13<03:38, 36.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7287/15290 [03:13<03:52, 34.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7291/15290 [03:13<03:50, 34.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7295/15290 [03:13<03:43, 35.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7299/15290 [03:13<03:41, 36.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7303/15290 [03:13<03:39, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7307/15290 [03:13<03:35, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7311/15290 [03:13<03:38, 36.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7315/15290 [03:14<03:38, 36.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7319/15290 [03:14<03:35, 36.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7323/15290 [03:14<03:43, 35.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7327/15290 [03:14<03:41, 36.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7331/15290 [03:14<03:39, 36.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7335/15290 [03:14<03:52, 34.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7339/15290 [03:14<03:44, 35.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7343/15290 [03:14<03:39, 36.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7347/15290 [03:14<03:46, 35.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7351/15290 [03:15<03:49, 34.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7355/15290 [03:15<03:42, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7359/15290 [03:15<03:45, 35.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7363/15290 [03:15<03:42, 35.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7367/15290 [03:15<03:54, 33.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7371/15290 [03:15<03:54, 33.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7375/15290 [03:15<03:49, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7379/15290 [03:15<03:47, 34.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7383/15290 [03:15<03:43, 35.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7387/15290 [03:16<03:39, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7391/15290 [03:16<03:36, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7395/15290 [03:16<04:07, 31.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7399/15290 [03:16<03:57, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7403/15290 [03:16<03:57, 33.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7407/15290 [03:16<03:54, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7411/15290 [03:16<03:49, 34.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7415/15290 [03:16<03:41, 35.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7419/15290 [03:17<03:40, 35.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7423/15290 [03:17<03:36, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7427/15290 [03:17<03:41, 35.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7431/15290 [03:17<03:41, 35.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7435/15290 [03:17<03:38, 35.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7439/15290 [03:17<03:33, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7443/15290 [03:17<03:31, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7447/15290 [03:17<03:28, 37.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7451/15290 [03:17<03:25, 38.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7455/15290 [03:18<03:23, 38.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7459/15290 [03:18<03:23, 38.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7463/15290 [03:18<03:56, 33.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7467/15290 [03:18<04:15, 30.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7471/15290 [03:18<04:08, 31.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7475/15290 [03:18<04:12, 30.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7479/15290 [03:18<04:07, 31.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7483/15290 [03:18<03:58, 32.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7487/15290 [03:19<03:51, 33.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7491/15290 [03:19<03:54, 33.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7495/15290 [03:19<04:04, 31.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7499/15290 [03:19<03:59, 32.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7503/15290 [03:19<03:48, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7507/15290 [03:19<03:45, 34.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7511/15290 [03:19<03:46, 34.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7515/15290 [03:19<03:43, 34.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7519/15290 [03:19<03:40, 35.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7523/15290 [03:20<03:46, 34.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7527/15290 [03:20<03:39, 35.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7531/15290 [03:20<03:42, 34.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7535/15290 [03:20<03:47, 34.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7539/15290 [03:20<03:44, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7543/15290 [03:20<03:43, 34.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7547/15290 [03:20<03:41, 34.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7551/15290 [03:20<03:44, 34.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7555/15290 [03:20<03:42, 34.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7559/15290 [03:21<03:42, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7563/15290 [03:21<03:44, 34.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7567/15290 [03:21<03:40, 35.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7571/15290 [03:21<03:42, 34.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7575/15290 [03:21<03:35, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7579/15290 [03:21<03:41, 34.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7583/15290 [03:21<03:44, 34.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7587/15290 [03:21<03:37, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7591/15290 [03:22<03:33, 36.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7595/15290 [03:22<03:32, 36.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7599/15290 [03:22<03:47, 33.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7603/15290 [03:22<03:45, 34.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7607/15290 [03:22<03:40, 34.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7611/15290 [03:22<03:46, 33.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7615/15290 [03:22<03:39, 35.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7619/15290 [03:22<03:41, 34.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7623/15290 [03:22<03:45, 34.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7627/15290 [03:23<03:43, 34.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7631/15290 [03:23<03:43, 34.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7635/15290 [03:23<03:52, 32.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7639/15290 [03:23<03:46, 33.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7643/15290 [03:23<03:44, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7647/15290 [03:23<03:41, 34.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7651/15290 [03:23<03:41, 34.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7655/15290 [03:23<03:46, 33.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7659/15290 [03:24<03:38, 34.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7663/15290 [03:24<03:44, 34.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7667/15290 [03:24<03:44, 33.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7671/15290 [03:24<03:34, 35.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7675/15290 [03:24<03:38, 34.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7679/15290 [03:24<03:31, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7683/15290 [03:24<03:30, 36.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7687/15290 [03:24<03:31, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7691/15290 [03:24<03:33, 35.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7695/15290 [03:25<03:29, 36.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7699/15290 [03:25<03:31, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7703/15290 [03:25<03:29, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7707/15290 [03:25<03:34, 35.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7711/15290 [03:25<03:33, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7715/15290 [03:25<03:31, 35.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7719/15290 [03:25<03:39, 34.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7723/15290 [03:25<03:35, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7727/15290 [03:25<03:35, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7731/15290 [03:26<03:36, 34.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7735/15290 [03:26<03:57, 31.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7739/15290 [03:26<03:51, 32.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7743/15290 [03:26<03:46, 33.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7747/15290 [03:26<03:38, 34.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7751/15290 [03:26<03:33, 35.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7755/15290 [03:26<03:33, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7759/15290 [03:26<03:29, 36.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7763/15290 [03:26<03:26, 36.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7767/15290 [03:27<03:21, 37.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7771/15290 [03:27<03:19, 37.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7776/15290 [03:27<03:14, 38.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7780/15290 [03:27<03:15, 38.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7784/15290 [03:27<03:23, 36.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7788/15290 [03:27<03:31, 35.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7792/15290 [03:27<03:39, 34.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7796/15290 [03:27<03:33, 35.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7800/15290 [03:27<03:37, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7804/15290 [03:28<03:34, 34.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7808/15290 [03:28<03:31, 35.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7812/15290 [03:28<03:35, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7816/15290 [03:28<03:39, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7820/15290 [03:28<03:35, 34.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7824/15290 [03:28<03:31, 35.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7828/15290 [03:28<03:24, 36.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7832/15290 [03:28<03:30, 35.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7836/15290 [03:29<03:29, 35.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7840/15290 [03:29<03:28, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7844/15290 [03:29<03:30, 35.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7848/15290 [03:29<03:28, 35.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7852/15290 [03:29<03:25, 36.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7856/15290 [03:29<03:24, 36.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7860/15290 [03:29<03:19, 37.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7864/15290 [03:29<03:18, 37.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7868/15290 [03:29<03:18, 37.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7872/15290 [03:29<03:18, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7876/15290 [03:30<03:21, 36.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7880/15290 [03:30<03:35, 34.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7884/15290 [03:30<03:44, 32.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7888/15290 [03:30<03:44, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7892/15290 [03:30<03:37, 34.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7896/15290 [03:30<03:43, 33.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7900/15290 [03:30<03:52, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7904/15290 [03:30<03:46, 32.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7908/15290 [03:31<03:35, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7912/15290 [03:31<03:46, 32.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7916/15290 [03:31<03:46, 32.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7920/15290 [03:31<03:37, 33.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7924/15290 [03:31<03:32, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7928/15290 [03:31<03:28, 35.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7932/15290 [03:31<03:30, 35.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7936/15290 [03:31<03:30, 34.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7940/15290 [03:32<03:31, 34.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7944/15290 [03:32<03:30, 34.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7948/15290 [03:32<03:30, 34.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7952/15290 [03:32<03:28, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7956/15290 [03:32<03:23, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7960/15290 [03:32<03:21, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7964/15290 [03:32<03:21, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7968/15290 [03:32<03:20, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7972/15290 [03:32<03:22, 36.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7976/15290 [03:32<03:22, 36.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7980/15290 [03:33<03:27, 35.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7984/15290 [03:33<03:23, 35.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7988/15290 [03:33<03:24, 35.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7993/15290 [03:33<03:15, 37.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7997/15290 [03:33<03:14, 37.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8001/15290 [03:33<03:12, 37.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8005/15290 [03:33<03:18, 36.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8009/15290 [03:33<03:25, 35.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8013/15290 [03:34<03:34, 33.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8017/15290 [03:34<03:26, 35.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8021/15290 [03:34<03:18, 36.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8025/15290 [03:34<03:18, 36.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8029/15290 [03:34<03:16, 36.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8033/15290 [03:34<03:19, 36.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8037/15290 [03:34<03:17, 36.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8041/15290 [03:34<03:14, 37.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8045/15290 [03:34<03:16, 36.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8049/15290 [03:34<03:14, 37.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8053/15290 [03:35<03:18, 36.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8057/15290 [03:35<03:18, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8061/15290 [03:35<03:20, 36.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8065/15290 [03:35<03:20, 35.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8069/15290 [03:35<03:20, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8073/15290 [03:35<03:17, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8077/15290 [03:35<03:17, 36.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8081/15290 [03:35<03:16, 36.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8085/15290 [03:35<03:13, 37.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8089/15290 [03:36<03:15, 36.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8093/15290 [03:36<03:15, 36.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8097/15290 [03:36<03:15, 36.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8101/15290 [03:36<03:18, 36.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8105/15290 [03:36<03:16, 36.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8109/15290 [03:36<03:19, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8113/15290 [03:36<03:18, 36.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8117/15290 [03:36<03:18, 36.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8121/15290 [03:36<03:15, 36.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8125/15290 [03:37<03:15, 36.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8129/15290 [03:37<03:19, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8133/15290 [03:37<03:19, 35.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8137/15290 [03:37<03:16, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8141/15290 [03:37<03:16, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8145/15290 [03:37<03:15, 36.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8149/15290 [03:37<03:17, 36.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8153/15290 [03:37<03:20, 35.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8157/15290 [03:37<03:18, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8161/15290 [03:38<03:17, 36.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8165/15290 [03:38<03:14, 36.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8169/15290 [03:38<03:11, 37.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8173/15290 [03:38<03:14, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8177/15290 [03:38<03:17, 36.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8181/15290 [03:38<03:14, 36.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8185/15290 [03:38<03:12, 36.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8189/15290 [03:38<03:11, 37.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8193/15290 [03:38<03:10, 37.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8197/15290 [03:39<03:11, 37.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8201/15290 [03:39<03:08, 37.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8205/15290 [03:39<03:09, 37.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8209/15290 [03:39<03:14, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8213/15290 [03:39<03:23, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8217/15290 [03:39<03:26, 34.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8221/15290 [03:39<03:29, 33.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8225/15290 [03:39<03:24, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8229/15290 [03:39<03:19, 35.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8233/15290 [03:40<03:12, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8237/15290 [03:40<03:10, 36.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8241/15290 [03:40<03:11, 36.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8245/15290 [03:40<03:09, 37.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8249/15290 [03:40<03:09, 37.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8253/15290 [03:40<03:08, 37.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8257/15290 [03:40<03:13, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8261/15290 [03:40<03:17, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8265/15290 [03:40<03:24, 34.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8269/15290 [03:41<03:28, 33.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8273/15290 [03:41<03:33, 32.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8277/15290 [03:41<03:32, 32.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8281/15290 [03:41<03:32, 33.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8285/15290 [03:41<03:32, 32.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8289/15290 [03:41<03:36, 32.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8293/15290 [03:41<03:32, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8297/15290 [03:41<03:27, 33.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8301/15290 [03:42<03:19, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8305/15290 [03:42<03:14, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8309/15290 [03:42<03:13, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8313/15290 [03:42<03:13, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8317/15290 [03:42<03:10, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8321/15290 [03:42<03:08, 36.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8325/15290 [03:42<03:07, 37.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8329/15290 [03:42<03:06, 37.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8333/15290 [03:42<03:06, 37.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8337/15290 [03:43<03:06, 37.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8341/15290 [03:43<03:10, 36.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8345/15290 [03:43<03:15, 35.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8349/15290 [03:43<03:12, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8353/15290 [03:43<03:12, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8357/15290 [03:43<03:13, 35.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8361/15290 [03:43<03:11, 36.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8365/15290 [03:43<03:08, 36.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8369/15290 [03:43<03:12, 35.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8373/15290 [03:44<03:09, 36.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8377/15290 [03:44<03:09, 36.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8381/15290 [03:44<03:04, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8385/15290 [03:44<03:05, 37.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8389/15290 [03:44<03:06, 36.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8393/15290 [03:44<03:08, 36.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8397/15290 [03:44<03:09, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8401/15290 [03:44<03:07, 36.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8405/15290 [03:44<03:06, 37.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8409/15290 [03:44<03:06, 36.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8413/15290 [03:45<03:08, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8417/15290 [03:45<03:10, 36.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8421/15290 [03:45<03:13, 35.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8425/15290 [03:45<03:10, 36.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8429/15290 [03:45<03:07, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8433/15290 [03:45<03:04, 37.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8437/15290 [03:45<03:05, 36.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8441/15290 [03:45<03:04, 37.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8445/15290 [03:45<03:09, 36.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8449/15290 [03:46<03:15, 34.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8453/15290 [03:46<03:12, 35.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8457/15290 [03:46<03:11, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8461/15290 [03:46<03:08, 36.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8465/15290 [03:46<03:08, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8469/15290 [03:46<03:07, 36.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8473/15290 [03:46<03:10, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8477/15290 [03:46<03:07, 36.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8481/15290 [03:46<03:03, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8485/15290 [03:47<03:04, 36.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8489/15290 [03:47<03:10, 35.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8493/15290 [03:47<03:16, 34.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8497/15290 [03:47<03:12, 35.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8501/15290 [03:47<03:09, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8505/15290 [03:47<03:10, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8509/15290 [03:47<03:05, 36.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8513/15290 [03:47<03:01, 37.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8517/15290 [03:47<03:02, 37.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8521/15290 [03:48<03:07, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8525/15290 [03:48<03:31, 31.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8529/15290 [03:48<03:38, 30.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8533/15290 [03:48<03:25, 32.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8537/15290 [03:48<03:18, 34.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8541/15290 [03:48<03:20, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8545/15290 [03:48<03:14, 34.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8549/15290 [03:48<03:09, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8553/15290 [03:49<03:08, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8557/15290 [03:49<03:06, 36.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8561/15290 [03:49<03:09, 35.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8565/15290 [03:49<03:10, 35.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8569/15290 [03:49<03:06, 36.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8573/15290 [03:49<03:04, 36.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8577/15290 [03:49<03:04, 36.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8581/15290 [03:49<03:03, 36.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8585/15290 [03:49<03:05, 36.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8589/15290 [03:50<03:04, 36.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8593/15290 [03:50<03:02, 36.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8597/15290 [03:50<03:11, 34.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8601/15290 [03:50<03:16, 34.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8605/15290 [03:50<03:13, 34.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8609/15290 [03:50<03:11, 34.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8613/15290 [03:50<03:13, 34.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8617/15290 [03:50<03:17, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8621/15290 [03:50<03:13, 34.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8625/15290 [03:51<03:15, 34.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8629/15290 [03:51<03:11, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8633/15290 [03:51<03:20, 33.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8637/15290 [03:51<03:20, 33.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8641/15290 [03:51<03:20, 33.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8645/15290 [03:51<03:25, 32.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8649/15290 [03:51<03:24, 32.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8653/15290 [03:51<03:28, 31.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8657/15290 [03:52<03:27, 32.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8661/15290 [03:52<03:34, 30.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8665/15290 [03:52<03:35, 30.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8669/15290 [03:52<03:30, 31.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8673/15290 [03:52<03:28, 31.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8677/15290 [03:52<03:54, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8681/15290 [03:52<03:45, 29.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8685/15290 [03:53<03:35, 30.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8689/15290 [03:53<03:28, 31.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8693/15290 [03:53<03:20, 32.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8697/15290 [03:53<03:24, 32.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8701/15290 [03:53<03:20, 32.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8705/15290 [03:53<03:18, 33.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8709/15290 [03:53<03:19, 32.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8713/15290 [03:53<03:15, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8717/15290 [03:53<03:14, 33.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8721/15290 [03:54<03:11, 34.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8725/15290 [03:54<03:11, 34.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8729/15290 [03:54<03:09, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8733/15290 [03:54<03:17, 33.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8737/15290 [03:54<03:14, 33.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8741/15290 [03:54<03:13, 33.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8745/15290 [03:54<03:19, 32.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8749/15290 [03:54<03:36, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8753/15290 [03:55<03:51, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8757/15290 [03:55<03:37, 29.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8761/15290 [03:55<03:30, 31.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8765/15290 [03:55<03:24, 31.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8769/15290 [03:55<03:19, 32.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8773/15290 [03:55<03:24, 31.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8777/15290 [03:55<03:18, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8781/15290 [03:55<03:17, 32.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8785/15290 [03:56<03:13, 33.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8789/15290 [03:56<03:17, 32.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8793/15290 [03:56<03:14, 33.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8797/15290 [03:56<03:12, 33.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8801/15290 [03:56<03:08, 34.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8805/15290 [03:56<03:04, 35.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8809/15290 [03:56<03:00, 35.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8813/15290 [03:56<02:59, 36.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8817/15290 [03:56<02:54, 37.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8821/15290 [03:57<02:54, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8825/15290 [03:57<02:53, 37.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8829/15290 [03:57<03:07, 34.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8833/15290 [03:57<03:10, 33.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8837/15290 [03:57<03:14, 33.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8841/15290 [03:57<03:17, 32.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8845/15290 [03:57<03:19, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8849/15290 [03:57<03:18, 32.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8853/15290 [03:58<03:18, 32.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8857/15290 [03:58<03:22, 31.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8861/15290 [03:58<03:18, 32.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8865/15290 [03:58<03:21, 31.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8869/15290 [03:58<03:17, 32.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8873/15290 [03:58<03:16, 32.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8877/15290 [03:58<03:11, 33.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8881/15290 [03:58<03:08, 33.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8885/15290 [03:59<03:03, 34.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8889/15290 [03:59<03:05, 34.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8893/15290 [03:59<03:05, 34.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8897/15290 [03:59<03:01, 35.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8901/15290 [03:59<02:59, 35.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8905/15290 [03:59<02:58, 35.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8909/15290 [03:59<03:06, 34.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8913/15290 [03:59<03:04, 34.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8917/15290 [03:59<03:08, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8921/15290 [04:00<03:05, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8925/15290 [04:00<03:09, 33.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8929/15290 [04:00<03:09, 33.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8933/15290 [04:00<03:10, 33.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8937/15290 [04:00<03:08, 33.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8941/15290 [04:00<03:08, 33.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8945/15290 [04:00<03:04, 34.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8949/15290 [04:00<03:05, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8953/15290 [04:01<03:16, 32.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8957/15290 [04:01<03:13, 32.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8961/15290 [04:01<03:09, 33.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8965/15290 [04:01<03:05, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8969/15290 [04:01<03:00, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8973/15290 [04:01<02:59, 35.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8977/15290 [04:01<03:02, 34.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8981/15290 [04:01<03:00, 35.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 8985/15290 [04:01<02:58, 35.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 8989/15290 [04:02<02:54, 36.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 8993/15290 [04:02<02:53, 36.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 8997/15290 [04:02<02:51, 36.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9001/15290 [04:02<02:51, 36.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9005/15290 [04:02<02:56, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9009/15290 [04:02<02:58, 35.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9013/15290 [04:02<02:56, 35.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9017/15290 [04:02<02:54, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9021/15290 [04:02<02:52, 36.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9025/15290 [04:03<02:52, 36.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9029/15290 [04:03<02:56, 35.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9033/15290 [04:03<02:58, 35.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9037/15290 [04:03<02:53, 36.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9041/15290 [04:03<02:54, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9045/15290 [04:03<02:56, 35.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9049/15290 [04:03<03:09, 32.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9053/15290 [04:03<03:04, 33.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9057/15290 [04:03<02:58, 34.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9061/15290 [04:04<02:54, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9065/15290 [04:04<02:56, 35.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9069/15290 [04:04<02:57, 34.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9073/15290 [04:04<02:55, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9077/15290 [04:04<02:54, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9081/15290 [04:04<02:51, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9085/15290 [04:04<02:50, 36.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9089/15290 [04:04<02:52, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9093/15290 [04:04<02:49, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9097/15290 [04:05<02:48, 36.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9101/15290 [04:05<02:46, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9105/15290 [04:05<02:49, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9109/15290 [04:05<02:52, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9113/15290 [04:05<02:53, 35.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9117/15290 [04:05<02:54, 35.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9121/15290 [04:05<02:52, 35.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9125/15290 [04:05<02:47, 36.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9129/15290 [04:05<02:45, 37.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9133/15290 [04:06<02:47, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9137/15290 [04:06<02:46, 36.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9141/15290 [04:06<02:54, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9145/15290 [04:06<03:02, 33.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9149/15290 [04:06<02:59, 34.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9153/15290 [04:06<03:01, 33.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9157/15290 [04:06<03:01, 33.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9161/15290 [04:06<02:57, 34.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9165/15290 [04:06<03:02, 33.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9169/15290 [04:07<03:04, 33.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9173/15290 [04:07<03:02, 33.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9177/15290 [04:07<03:01, 33.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9181/15290 [04:07<03:01, 33.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9185/15290 [04:07<03:04, 33.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9189/15290 [04:07<03:06, 32.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9193/15290 [04:07<03:11, 31.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9197/15290 [04:07<03:04, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9201/15290 [04:08<03:07, 32.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9205/15290 [04:08<03:11, 31.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9209/15290 [04:08<03:21, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9213/15290 [04:08<03:16, 30.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9217/15290 [04:08<03:11, 31.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9221/15290 [04:08<03:12, 31.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9225/15290 [04:08<03:10, 31.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9229/15290 [04:08<03:11, 31.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9233/15290 [04:09<03:23, 29.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9237/15290 [04:09<03:19, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9241/15290 [04:09<03:15, 30.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9245/15290 [04:09<03:06, 32.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9249/15290 [04:09<03:05, 32.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9253/15290 [04:09<03:02, 33.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9257/15290 [04:09<03:01, 33.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9261/15290 [04:10<04:09, 24.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9264/15290 [04:10<04:33, 22.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9267/15290 [04:10<04:38, 21.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9270/15290 [04:10<04:28, 22.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9274/15290 [04:10<03:58, 25.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9278/15290 [04:10<03:36, 27.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9282/15290 [04:10<03:17, 30.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9286/15290 [04:11<03:11, 31.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9290/15290 [04:11<03:05, 32.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9294/15290 [04:11<03:12, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9298/15290 [04:11<03:14, 30.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9302/15290 [04:11<03:08, 31.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9306/15290 [04:11<03:01, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9310/15290 [04:11<02:59, 33.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9314/15290 [04:11<02:55, 34.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9318/15290 [04:11<02:48, 35.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9322/15290 [04:12<02:50, 35.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9326/15290 [04:12<02:49, 35.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9330/15290 [04:12<02:56, 33.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9334/15290 [04:12<03:00, 32.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9338/15290 [04:12<03:04, 32.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9342/15290 [04:12<03:07, 31.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9346/15290 [04:12<03:09, 31.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9350/15290 [04:12<03:08, 31.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9354/15290 [04:13<03:09, 31.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9358/15290 [04:13<03:08, 31.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9362/15290 [04:13<03:05, 31.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9366/15290 [04:13<03:03, 32.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9370/15290 [04:13<03:00, 32.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9374/15290 [04:13<02:58, 33.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9378/15290 [04:13<03:02, 32.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9382/15290 [04:13<03:00, 32.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9386/15290 [04:14<02:54, 33.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9390/15290 [04:14<02:54, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9394/15290 [04:14<02:51, 34.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9398/15290 [04:14<02:47, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9402/15290 [04:14<02:46, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9406/15290 [04:14<02:44, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9410/15290 [04:14<02:51, 34.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9414/15290 [04:14<02:48, 34.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9418/15290 [04:14<02:45, 35.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9422/15290 [04:15<02:58, 32.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9426/15290 [04:15<02:54, 33.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9430/15290 [04:15<02:48, 34.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9434/15290 [04:15<02:46, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9438/15290 [04:15<02:44, 35.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9442/15290 [04:15<02:45, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9446/15290 [04:15<02:44, 35.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9450/15290 [04:15<02:44, 35.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9454/15290 [04:16<02:45, 35.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9458/15290 [04:16<02:49, 34.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9462/15290 [04:16<02:51, 34.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9466/15290 [04:16<02:51, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9470/15290 [04:16<02:51, 33.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9474/15290 [04:16<02:50, 34.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9478/15290 [04:16<02:45, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9482/15290 [04:16<02:45, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9486/15290 [04:16<02:47, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9490/15290 [04:17<02:41, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9494/15290 [04:17<02:40, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9498/15290 [04:17<02:42, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9502/15290 [04:17<02:42, 35.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9506/15290 [04:17<02:42, 35.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9510/15290 [04:17<02:44, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9514/15290 [04:17<02:49, 33.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9518/15290 [04:17<02:58, 32.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9522/15290 [04:17<02:52, 33.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9526/15290 [04:18<02:47, 34.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9530/15290 [04:18<02:49, 33.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9534/15290 [04:18<02:48, 34.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9538/15290 [04:18<02:54, 33.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9542/15290 [04:18<02:53, 33.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9546/15290 [04:18<02:55, 32.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9550/15290 [04:18<02:58, 32.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9554/15290 [04:18<02:58, 32.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9558/15290 [04:19<03:00, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9562/15290 [04:19<02:58, 32.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9566/15290 [04:19<02:56, 32.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9570/15290 [04:19<02:47, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9574/15290 [04:19<02:47, 34.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9578/15290 [04:19<02:45, 34.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9582/15290 [04:19<02:43, 34.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9586/15290 [04:19<02:44, 34.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9590/15290 [04:20<02:41, 35.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9594/15290 [04:20<02:39, 35.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9598/15290 [04:20<02:41, 35.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9602/15290 [04:20<02:41, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9606/15290 [04:20<02:42, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9610/15290 [04:20<02:39, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9614/15290 [04:20<02:37, 36.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9618/15290 [04:20<02:35, 36.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9622/15290 [04:20<02:33, 36.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9626/15290 [04:21<02:36, 36.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9630/15290 [04:21<02:35, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9634/15290 [04:21<02:33, 36.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9638/15290 [04:21<02:33, 36.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9642/15290 [04:21<02:41, 35.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9646/15290 [04:21<02:42, 34.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9650/15290 [04:21<02:42, 34.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9654/15290 [04:21<02:42, 34.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9658/15290 [04:21<02:40, 35.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9662/15290 [04:22<02:37, 35.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9666/15290 [04:22<02:35, 36.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9670/15290 [04:22<02:45, 33.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9674/15290 [04:22<02:45, 33.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9678/15290 [04:22<02:42, 34.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9682/15290 [04:22<02:41, 34.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9686/15290 [04:22<02:37, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9690/15290 [04:22<02:37, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9694/15290 [04:22<02:40, 34.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9698/15290 [04:23<02:42, 34.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9702/15290 [04:23<02:43, 34.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9706/15290 [04:23<02:44, 33.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9710/15290 [04:23<02:45, 33.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9714/15290 [04:23<02:49, 32.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9718/15290 [04:23<02:50, 32.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9722/15290 [04:23<02:56, 31.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9726/15290 [04:23<02:53, 32.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9730/15290 [04:24<02:49, 32.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9734/15290 [04:24<02:48, 32.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9738/15290 [04:24<02:52, 32.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9742/15290 [04:24<02:51, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9746/15290 [04:24<02:55, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9750/15290 [04:24<02:54, 31.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9754/15290 [04:24<02:56, 31.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9758/15290 [04:24<03:01, 30.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9762/15290 [04:25<02:56, 31.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9766/15290 [04:25<03:05, 29.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9770/15290 [04:25<03:02, 30.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9774/15290 [04:25<02:56, 31.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9778/15290 [04:25<02:49, 32.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9782/15290 [04:25<02:49, 32.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9786/15290 [04:25<02:49, 32.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9790/15290 [04:25<02:42, 33.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9794/15290 [04:26<02:41, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9798/15290 [04:26<02:42, 33.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9802/15290 [04:26<02:46, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9806/15290 [04:26<02:49, 32.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9810/15290 [04:26<02:49, 32.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9814/15290 [04:26<02:47, 32.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9818/15290 [04:26<02:54, 31.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9822/15290 [04:26<02:53, 31.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9826/15290 [04:27<02:53, 31.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9830/15290 [04:27<02:52, 31.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9834/15290 [04:27<02:56, 30.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9838/15290 [04:27<02:56, 30.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9842/15290 [04:27<02:56, 30.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9846/15290 [04:27<02:52, 31.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9850/15290 [04:27<02:54, 31.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9854/15290 [04:27<02:49, 32.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9858/15290 [04:28<02:49, 32.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9862/15290 [04:28<02:47, 32.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9866/15290 [04:28<02:50, 31.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9870/15290 [04:28<02:43, 33.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9874/15290 [04:28<02:38, 34.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9878/15290 [04:28<02:38, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9882/15290 [04:28<02:35, 34.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9886/15290 [04:28<02:34, 34.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9890/15290 [04:29<02:34, 34.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9894/15290 [04:29<02:36, 34.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9898/15290 [04:29<02:32, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9902/15290 [04:29<02:31, 35.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9906/15290 [04:29<02:28, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9910/15290 [04:29<02:28, 36.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9914/15290 [04:29<02:29, 36.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9918/15290 [04:29<02:31, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9922/15290 [04:29<02:29, 35.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9926/15290 [04:30<02:28, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9930/15290 [04:30<02:27, 36.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9934/15290 [04:30<02:28, 36.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9938/15290 [04:30<02:28, 36.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9942/15290 [04:30<02:27, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9946/15290 [04:30<02:32, 35.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9950/15290 [04:30<02:42, 32.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9954/15290 [04:30<02:40, 33.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9958/15290 [04:30<02:39, 33.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9962/15290 [04:31<02:41, 33.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9966/15290 [04:31<02:44, 32.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9970/15290 [04:31<02:50, 31.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9974/15290 [04:31<03:18, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9978/15290 [04:31<03:02, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9982/15290 [04:31<02:54, 30.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9986/15290 [04:31<02:47, 31.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9990/15290 [04:31<02:40, 33.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9994/15290 [04:32<02:39, 33.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9998/15290 [04:32<02:47, 31.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 10002/15290 [04:32<02:43, 32.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 10006/15290 [04:32<02:37, 33.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 10010/15290 [04:32<02:33, 34.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 10014/15290 [04:32<02:35, 34.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10018/15290 [04:32<02:30, 34.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10022/15290 [04:32<02:30, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10026/15290 [04:33<02:31, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10030/15290 [04:33<02:35, 33.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10034/15290 [04:33<02:35, 33.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10038/15290 [04:33<02:34, 33.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10042/15290 [04:33<02:31, 34.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10046/15290 [04:33<02:31, 34.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10050/15290 [04:33<02:29, 35.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10054/15290 [04:33<02:36, 33.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10058/15290 [04:33<02:34, 33.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10062/15290 [04:34<02:39, 32.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10066/15290 [04:34<02:39, 32.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10070/15290 [04:34<02:34, 33.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10074/15290 [04:34<02:32, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10078/15290 [04:34<02:30, 34.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10082/15290 [04:34<02:30, 34.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10086/15290 [04:34<02:27, 35.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10090/15290 [04:34<02:27, 35.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10094/15290 [04:35<02:28, 35.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10098/15290 [04:35<02:29, 34.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10102/15290 [04:35<02:30, 34.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10106/15290 [04:35<02:30, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10110/15290 [04:35<02:30, 34.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10114/15290 [04:35<02:32, 33.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10118/15290 [04:35<02:32, 33.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10122/15290 [04:35<02:32, 33.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10126/15290 [04:35<02:33, 33.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10130/15290 [04:36<02:34, 33.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10134/15290 [04:36<02:31, 34.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10138/15290 [04:36<02:36, 33.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10142/15290 [04:36<02:38, 32.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10146/15290 [04:36<02:44, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10150/15290 [04:36<02:44, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10154/15290 [04:36<02:43, 31.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10158/15290 [04:36<02:40, 32.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10162/15290 [04:37<02:37, 32.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10166/15290 [04:37<02:31, 33.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10170/15290 [04:37<02:29, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10174/15290 [04:37<02:26, 34.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10178/15290 [04:37<02:25, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10182/15290 [04:37<02:30, 33.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10186/15290 [04:37<02:37, 32.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10190/15290 [04:37<02:41, 31.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10194/15290 [04:38<02:37, 32.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10198/15290 [04:38<02:32, 33.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10202/15290 [04:38<02:38, 32.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10206/15290 [04:38<02:35, 32.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10210/15290 [04:38<02:31, 33.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10214/15290 [04:38<02:31, 33.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10218/15290 [04:38<02:28, 34.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10222/15290 [04:38<02:25, 34.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10226/15290 [04:38<02:21, 35.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10230/15290 [04:39<02:22, 35.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10234/15290 [04:39<02:24, 35.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10238/15290 [04:39<02:27, 34.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10242/15290 [04:39<02:26, 34.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10246/15290 [04:39<02:31, 33.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10250/15290 [04:39<02:32, 32.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10254/15290 [04:39<02:36, 32.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10258/15290 [04:39<02:41, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10262/15290 [04:40<02:37, 31.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10266/15290 [04:40<02:36, 32.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10270/15290 [04:40<02:41, 31.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10274/15290 [04:40<02:40, 31.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10278/15290 [04:40<02:41, 31.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10282/15290 [04:40<02:40, 31.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10286/15290 [04:40<02:44, 30.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10290/15290 [04:40<02:44, 30.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10294/15290 [04:41<02:47, 29.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10298/15290 [04:41<02:39, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10302/15290 [04:41<02:35, 32.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10306/15290 [04:41<02:36, 31.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10310/15290 [04:41<02:41, 30.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10314/15290 [04:41<02:44, 30.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10318/15290 [04:41<02:46, 29.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10322/15290 [04:42<02:39, 31.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10326/15290 [04:42<02:36, 31.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10330/15290 [04:42<02:33, 32.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10334/15290 [04:42<02:30, 32.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10338/15290 [04:42<02:33, 32.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10342/15290 [04:42<02:33, 32.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10346/15290 [04:42<02:34, 31.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10350/15290 [04:42<02:32, 32.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10354/15290 [04:43<02:32, 32.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10358/15290 [04:43<02:27, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10362/15290 [04:43<02:24, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10366/15290 [04:43<02:21, 34.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10370/15290 [04:43<02:18, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10374/15290 [04:43<02:25, 33.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10378/15290 [04:43<02:28, 33.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10382/15290 [04:43<02:26, 33.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10386/15290 [04:43<02:34, 31.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10390/15290 [04:44<02:32, 32.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10394/15290 [04:44<02:33, 31.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10398/15290 [04:44<02:29, 32.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10402/15290 [04:44<02:26, 33.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10406/15290 [04:44<02:24, 33.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10410/15290 [04:44<02:22, 34.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10414/15290 [04:44<02:19, 34.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10418/15290 [04:44<02:19, 34.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10422/15290 [04:45<02:30, 32.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10426/15290 [04:45<02:30, 32.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10430/15290 [04:45<02:27, 32.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10434/15290 [04:45<02:23, 33.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10438/15290 [04:45<02:20, 34.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10442/15290 [04:45<02:20, 34.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10446/15290 [04:45<02:21, 34.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10450/15290 [04:45<02:25, 33.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10454/15290 [04:45<02:26, 33.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10458/15290 [04:46<02:27, 32.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10462/15290 [04:46<02:24, 33.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10466/15290 [04:46<02:24, 33.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10470/15290 [04:46<02:24, 33.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10474/15290 [04:46<02:21, 33.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10478/15290 [04:46<02:20, 34.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10482/15290 [04:46<02:19, 34.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10486/15290 [04:46<02:19, 34.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10490/15290 [04:47<02:18, 34.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10494/15290 [04:47<02:18, 34.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10498/15290 [04:47<02:20, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10502/15290 [04:47<02:18, 34.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10506/15290 [04:47<02:18, 34.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10510/15290 [04:47<02:21, 33.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10514/15290 [04:47<02:18, 34.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10518/15290 [04:47<02:17, 34.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10522/15290 [04:47<02:16, 34.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10526/15290 [04:48<02:17, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10530/15290 [04:48<02:13, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10534/15290 [04:48<02:16, 34.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10538/15290 [04:48<02:16, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10542/15290 [04:48<02:15, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10546/15290 [04:48<02:14, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10550/15290 [04:48<02:16, 34.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10554/15290 [04:48<02:15, 34.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10558/15290 [04:48<02:15, 34.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10562/15290 [04:49<02:17, 34.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10566/15290 [04:49<02:16, 34.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10570/15290 [04:49<02:16, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10574/15290 [04:49<02:17, 34.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10578/15290 [04:49<02:14, 35.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10582/15290 [04:49<02:16, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10586/15290 [04:49<02:18, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10590/15290 [04:49<02:21, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10594/15290 [04:50<02:17, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10598/15290 [04:50<02:15, 34.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10602/15290 [04:50<02:17, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10606/15290 [04:50<02:19, 33.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10610/15290 [04:50<02:17, 33.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10614/15290 [04:50<02:16, 34.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10618/15290 [04:50<02:19, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10622/15290 [04:50<02:20, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10626/15290 [04:50<02:18, 33.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10630/15290 [04:51<02:18, 33.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10634/15290 [04:51<02:22, 32.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10638/15290 [04:51<02:19, 33.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10642/15290 [04:51<02:43, 28.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10646/15290 [04:51<02:38, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10650/15290 [04:51<02:35, 29.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10654/15290 [04:51<02:39, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10658/15290 [04:52<02:32, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10662/15290 [04:52<02:27, 31.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10666/15290 [04:52<02:25, 31.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10670/15290 [04:52<02:22, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10674/15290 [04:52<02:20, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10678/15290 [04:52<02:16, 33.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10682/15290 [04:52<02:15, 33.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10686/15290 [04:52<02:11, 34.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10690/15290 [04:52<02:11, 34.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10694/15290 [04:53<02:12, 34.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10698/15290 [04:53<02:11, 34.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10702/15290 [04:53<02:11, 34.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10706/15290 [04:53<02:08, 35.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10710/15290 [04:53<02:08, 35.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10714/15290 [04:53<02:12, 34.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10718/15290 [04:53<02:09, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10722/15290 [04:53<02:08, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10726/15290 [04:54<02:18, 33.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10730/15290 [04:54<02:19, 32.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10734/15290 [04:54<02:27, 30.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10738/15290 [04:54<02:26, 30.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10742/15290 [04:54<02:24, 31.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10746/15290 [04:54<02:23, 31.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10750/15290 [04:54<02:19, 32.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10754/15290 [04:54<02:20, 32.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10758/15290 [04:55<02:23, 31.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10762/15290 [04:55<02:18, 32.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10766/15290 [04:55<02:15, 33.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10770/15290 [04:55<02:14, 33.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10774/15290 [04:55<02:12, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10778/15290 [04:55<02:15, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10782/15290 [04:55<02:20, 32.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10786/15290 [04:55<02:20, 32.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10790/15290 [04:56<02:23, 31.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10794/15290 [04:56<02:24, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10798/15290 [04:56<02:24, 31.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10802/15290 [04:56<02:32, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10805/15290 [04:56<02:32, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10808/15290 [04:56<02:34, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10812/15290 [04:56<02:24, 30.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10816/15290 [04:56<02:20, 31.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10820/15290 [04:57<02:16, 32.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10824/15290 [04:57<02:15, 32.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10828/15290 [04:57<02:16, 32.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10832/15290 [04:57<02:20, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10836/15290 [04:57<02:21, 31.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10840/15290 [04:57<02:25, 30.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10844/15290 [04:57<02:28, 29.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10848/15290 [04:57<02:32, 29.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10851/15290 [04:58<02:32, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10854/15290 [04:58<02:32, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10857/15290 [04:58<02:34, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10861/15290 [04:58<02:27, 30.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10865/15290 [04:58<02:32, 29.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10868/15290 [04:58<02:36, 28.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10872/15290 [04:58<02:30, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10876/15290 [04:58<02:22, 30.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10880/15290 [04:59<02:21, 31.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10884/15290 [04:59<02:17, 32.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10888/15290 [04:59<02:13, 32.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10892/15290 [04:59<02:12, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10896/15290 [04:59<02:17, 31.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10900/15290 [04:59<02:19, 31.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10904/15290 [04:59<02:18, 31.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10908/15290 [04:59<02:22, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10912/15290 [05:00<02:23, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10916/15290 [05:00<02:26, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10919/15290 [05:00<02:29, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10923/15290 [05:00<02:26, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10927/15290 [05:00<02:19, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10931/15290 [05:00<02:14, 32.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10935/15290 [05:00<02:10, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10939/15290 [05:00<02:12, 32.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10943/15290 [05:00<02:11, 33.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10947/15290 [05:01<02:12, 32.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10951/15290 [05:01<02:08, 33.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10955/15290 [05:01<02:08, 33.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10959/15290 [05:01<02:05, 34.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10963/15290 [05:01<02:03, 35.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10967/15290 [05:01<02:12, 32.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10971/15290 [05:01<02:18, 31.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10975/15290 [05:01<02:23, 30.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10979/15290 [05:02<02:25, 29.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10982/15290 [05:02<02:37, 27.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10985/15290 [05:02<02:34, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10989/15290 [05:02<02:23, 29.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10993/15290 [05:02<02:15, 31.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10997/15290 [05:02<02:09, 33.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11001/15290 [05:02<02:06, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11005/15290 [05:02<02:03, 34.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11009/15290 [05:03<02:06, 33.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11013/15290 [05:03<02:05, 34.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11017/15290 [05:03<02:04, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11021/15290 [05:03<02:03, 34.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11025/15290 [05:03<02:21, 30.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11029/15290 [05:03<02:17, 30.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11033/15290 [05:03<02:16, 31.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11037/15290 [05:03<02:17, 30.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11041/15290 [05:04<02:15, 31.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11045/15290 [05:04<02:17, 30.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11049/15290 [05:04<02:14, 31.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11053/15290 [05:04<02:13, 31.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11057/15290 [05:04<02:12, 31.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11061/15290 [05:04<02:09, 32.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11065/15290 [05:04<02:07, 33.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11069/15290 [05:04<02:05, 33.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11073/15290 [05:05<02:05, 33.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11077/15290 [05:05<02:03, 33.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11081/15290 [05:05<02:02, 34.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11085/15290 [05:05<02:00, 34.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11089/15290 [05:05<02:01, 34.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11093/15290 [05:05<02:01, 34.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11097/15290 [05:05<02:02, 34.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11101/15290 [05:05<02:13, 31.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11105/15290 [05:05<02:08, 32.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11109/15290 [05:06<02:05, 33.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11113/15290 [05:06<02:05, 33.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11117/15290 [05:06<02:01, 34.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11121/15290 [05:06<02:00, 34.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11125/15290 [05:06<01:57, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11129/15290 [05:06<01:58, 34.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11133/15290 [05:06<01:58, 35.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11137/15290 [05:06<01:57, 35.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11141/15290 [05:07<01:58, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11145/15290 [05:07<02:02, 33.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11149/15290 [05:07<02:07, 32.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11153/15290 [05:07<02:05, 33.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11157/15290 [05:07<02:04, 33.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11161/15290 [05:07<02:02, 33.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11165/15290 [05:07<02:00, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11169/15290 [05:07<01:59, 34.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11173/15290 [05:07<01:59, 34.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11177/15290 [05:08<02:00, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11181/15290 [05:08<02:03, 33.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11185/15290 [05:08<02:04, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11189/15290 [05:08<02:03, 33.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11193/15290 [05:08<02:04, 32.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11197/15290 [05:08<02:07, 32.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11201/15290 [05:08<02:09, 31.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11205/15290 [05:08<02:07, 32.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11209/15290 [05:09<02:04, 32.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11213/15290 [05:09<02:03, 32.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11217/15290 [05:09<02:03, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11221/15290 [05:09<02:04, 32.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11225/15290 [05:09<02:00, 33.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11229/15290 [05:09<01:59, 34.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11233/15290 [05:09<01:58, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11237/15290 [05:09<01:58, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11241/15290 [05:10<01:57, 34.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11245/15290 [05:10<01:57, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11249/15290 [05:10<02:09, 31.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11253/15290 [05:10<02:10, 30.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11257/15290 [05:10<02:07, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11261/15290 [05:10<02:07, 31.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11265/15290 [05:10<02:12, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11269/15290 [05:10<02:13, 30.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11273/15290 [05:11<02:18, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11277/15290 [05:11<02:14, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11281/15290 [05:11<02:20, 28.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11285/15290 [05:11<02:15, 29.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11289/15290 [05:11<02:14, 29.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11292/15290 [05:11<02:14, 29.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11296/15290 [05:11<02:10, 30.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11300/15290 [05:11<02:06, 31.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11304/15290 [05:12<02:03, 32.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11308/15290 [05:12<02:06, 31.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11312/15290 [05:12<02:11, 30.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11316/15290 [05:12<02:41, 24.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11319/15290 [05:12<02:34, 25.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11323/15290 [05:12<02:21, 28.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11327/15290 [05:12<02:13, 29.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11331/15290 [05:13<02:11, 30.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11335/15290 [05:13<02:08, 30.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11339/15290 [05:13<02:07, 31.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11343/15290 [05:13<02:10, 30.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11347/15290 [05:13<02:08, 30.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11351/15290 [05:13<02:10, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11355/15290 [05:13<02:10, 30.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11359/15290 [05:13<02:12, 29.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11363/15290 [05:14<02:10, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11367/15290 [05:14<02:10, 30.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11371/15290 [05:14<02:10, 30.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11375/15290 [05:14<02:08, 30.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11379/15290 [05:14<02:05, 31.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11383/15290 [05:14<02:04, 31.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11387/15290 [05:14<02:12, 29.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11390/15290 [05:15<02:16, 28.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11393/15290 [05:15<02:17, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11397/15290 [05:15<02:14, 29.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11401/15290 [05:15<02:07, 30.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11405/15290 [05:15<02:05, 31.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11409/15290 [05:15<02:06, 30.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11413/15290 [05:15<02:06, 30.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11417/15290 [05:15<02:06, 30.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11421/15290 [05:16<02:07, 30.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11425/15290 [05:16<02:21, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11428/15290 [05:16<02:20, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11432/15290 [05:16<02:15, 28.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11436/15290 [05:16<02:07, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11440/15290 [05:16<02:01, 31.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11444/15290 [05:16<01:57, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11448/15290 [05:16<01:53, 33.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11452/15290 [05:17<01:54, 33.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11456/15290 [05:17<01:52, 34.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11460/15290 [05:17<01:52, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11464/15290 [05:17<01:50, 34.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11468/15290 [05:17<01:50, 34.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11472/15290 [05:17<01:55, 33.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11476/15290 [05:17<01:58, 32.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11480/15290 [05:17<01:59, 31.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11484/15290 [05:17<01:56, 32.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11488/15290 [05:18<01:57, 32.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11492/15290 [05:18<01:58, 32.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11496/15290 [05:18<01:59, 31.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11500/15290 [05:18<02:01, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11504/15290 [05:18<02:00, 31.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11508/15290 [05:18<02:05, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11512/15290 [05:18<02:04, 30.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11516/15290 [05:19<02:06, 29.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11519/15290 [05:19<02:06, 29.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11523/15290 [05:19<02:03, 30.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11527/15290 [05:19<02:00, 31.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11531/15290 [05:19<01:59, 31.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11535/15290 [05:19<01:54, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11539/15290 [05:19<01:53, 33.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11543/15290 [05:19<01:51, 33.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11547/15290 [05:19<01:52, 33.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11551/15290 [05:20<01:54, 32.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11555/15290 [05:20<01:57, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11559/15290 [05:20<02:00, 31.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11563/15290 [05:20<01:58, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11567/15290 [05:20<01:55, 32.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11571/15290 [05:20<01:56, 31.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11575/15290 [05:20<01:56, 31.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11579/15290 [05:20<01:57, 31.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11583/15290 [05:21<01:55, 32.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11587/15290 [05:21<01:56, 31.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11591/15290 [05:21<01:56, 31.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11595/15290 [05:21<01:56, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11599/15290 [05:21<01:52, 32.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11603/15290 [05:21<01:53, 32.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11607/15290 [05:21<01:52, 32.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11611/15290 [05:21<01:51, 32.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11615/15290 [05:22<01:50, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11619/15290 [05:22<01:48, 33.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11623/15290 [05:22<01:49, 33.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11627/15290 [05:22<01:48, 33.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11631/15290 [05:22<01:48, 33.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11635/15290 [05:22<01:47, 34.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11639/15290 [05:22<01:45, 34.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11643/15290 [05:22<01:45, 34.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11647/15290 [05:23<01:46, 34.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11651/15290 [05:23<01:49, 33.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11655/15290 [05:23<01:53, 32.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11659/15290 [05:23<01:53, 31.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11663/15290 [05:23<01:53, 31.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11667/15290 [05:23<01:55, 31.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11671/15290 [05:23<01:54, 31.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11675/15290 [05:23<01:55, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11679/15290 [05:24<01:57, 30.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11683/15290 [05:24<01:54, 31.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11687/15290 [05:24<01:56, 30.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11691/15290 [05:24<01:55, 31.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11695/15290 [05:24<01:56, 30.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11699/15290 [05:24<01:56, 30.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11703/15290 [05:24<01:55, 31.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11707/15290 [05:24<01:56, 30.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11711/15290 [05:25<01:56, 30.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11715/15290 [05:25<01:54, 31.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11719/15290 [05:25<01:52, 31.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11723/15290 [05:25<01:50, 32.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11727/15290 [05:25<01:48, 32.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11731/15290 [05:25<01:47, 32.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11735/15290 [05:25<01:47, 33.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11739/15290 [05:25<01:47, 33.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11743/15290 [05:26<01:49, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11747/15290 [05:26<01:52, 31.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11751/15290 [05:26<02:00, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11755/15290 [05:26<01:54, 30.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11759/15290 [05:26<01:54, 30.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11763/15290 [05:26<01:54, 30.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11767/15290 [05:26<01:52, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11771/15290 [05:26<01:52, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11775/15290 [05:27<01:51, 31.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11779/15290 [05:27<01:50, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11783/15290 [05:27<01:48, 32.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11787/15290 [05:27<01:46, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11791/15290 [05:27<01:53, 30.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11795/15290 [05:27<01:53, 30.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11799/15290 [05:27<01:57, 29.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11802/15290 [05:28<01:59, 29.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11806/15290 [05:28<01:57, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11809/15290 [05:28<02:01, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11812/15290 [05:28<02:04, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11815/15290 [05:28<02:02, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11819/15290 [05:28<02:01, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11823/15290 [05:28<01:58, 29.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11827/15290 [05:28<01:54, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11831/15290 [05:28<01:54, 30.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11835/15290 [05:29<01:55, 29.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11839/15290 [05:29<01:52, 30.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11843/15290 [05:29<01:49, 31.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11847/15290 [05:29<01:50, 31.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11851/15290 [05:29<01:53, 30.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11855/15290 [05:29<01:53, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11859/15290 [05:29<01:51, 30.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11863/15290 [05:30<01:49, 31.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11867/15290 [05:30<01:50, 30.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11871/15290 [05:30<01:55, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11874/15290 [05:30<02:03, 27.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11877/15290 [05:30<02:01, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11880/15290 [05:30<02:00, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11884/15290 [05:30<01:54, 29.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11888/15290 [05:30<01:48, 31.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11892/15290 [05:31<01:53, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11896/15290 [05:31<01:54, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11900/15290 [05:31<01:51, 30.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11904/15290 [05:31<01:51, 30.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11908/15290 [05:31<01:53, 29.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11912/15290 [05:31<01:53, 29.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11916/15290 [05:31<01:51, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11920/15290 [05:31<01:50, 30.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11924/15290 [05:32<01:49, 30.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11928/15290 [05:32<01:48, 30.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11932/15290 [05:32<01:55, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11936/15290 [05:32<01:50, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11940/15290 [05:32<01:47, 31.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11944/15290 [05:32<01:43, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11948/15290 [05:32<01:45, 31.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11952/15290 [05:32<01:49, 30.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11956/15290 [05:33<01:48, 30.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11960/15290 [05:33<01:45, 31.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11964/15290 [05:33<01:42, 32.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11968/15290 [05:33<01:39, 33.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11972/15290 [05:33<01:39, 33.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11976/15290 [05:33<01:41, 32.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11980/15290 [05:33<01:45, 31.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11984/15290 [05:33<01:44, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11988/15290 [05:34<01:42, 32.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11992/15290 [05:34<01:45, 31.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11996/15290 [05:34<01:50, 29.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 12000/15290 [05:34<01:48, 30.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12004/15290 [05:34<01:45, 31.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12008/15290 [05:34<01:48, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12012/15290 [05:34<01:48, 30.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12016/15290 [05:35<01:47, 30.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12020/15290 [05:35<01:46, 30.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12024/15290 [05:35<01:44, 31.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12028/15290 [05:35<01:43, 31.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12032/15290 [05:35<01:41, 32.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12036/15290 [05:35<01:39, 32.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12040/15290 [05:35<01:37, 33.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12044/15290 [05:35<01:35, 33.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12048/15290 [05:35<01:36, 33.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12052/15290 [05:36<01:34, 34.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12056/15290 [05:36<01:35, 33.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12060/15290 [05:36<01:40, 32.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12064/15290 [05:36<01:45, 30.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12068/15290 [05:36<01:45, 30.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12072/15290 [05:36<01:47, 30.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12076/15290 [05:36<01:52, 28.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12079/15290 [05:37<02:02, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12083/15290 [05:37<01:56, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12087/15290 [05:37<01:49, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12091/15290 [05:37<01:44, 30.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12095/15290 [05:37<01:40, 31.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12099/15290 [05:37<01:37, 32.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12103/15290 [05:37<01:36, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12107/15290 [05:37<01:43, 30.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12111/15290 [05:38<01:48, 29.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12115/15290 [05:38<01:44, 30.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12119/15290 [05:38<01:40, 31.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12123/15290 [05:38<01:39, 31.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12127/15290 [05:38<01:36, 32.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12131/15290 [05:38<01:37, 32.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12135/15290 [05:38<01:35, 32.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12139/15290 [05:38<01:35, 32.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12143/15290 [05:39<01:36, 32.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12147/15290 [05:39<01:46, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12151/15290 [05:39<01:46, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12154/15290 [05:39<01:48, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12157/15290 [05:39<01:52, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12161/15290 [05:39<01:46, 29.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12164/15290 [05:39<01:51, 27.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12167/15290 [05:39<02:05, 24.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12170/15290 [05:40<02:15, 23.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12173/15290 [05:40<02:28, 21.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12176/15290 [05:40<02:27, 21.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12179/15290 [05:40<02:17, 22.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12182/15290 [05:40<02:13, 23.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12185/15290 [05:40<02:12, 23.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12189/15290 [05:40<02:00, 25.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12192/15290 [05:41<02:10, 23.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12195/15290 [05:41<02:03, 24.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12199/15290 [05:41<01:52, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12203/15290 [05:41<01:44, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12207/15290 [05:41<01:40, 30.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12211/15290 [05:41<01:38, 31.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12215/15290 [05:41<01:34, 32.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12219/15290 [05:41<01:30, 33.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12223/15290 [05:42<01:31, 33.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12227/15290 [05:42<01:32, 32.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12231/15290 [05:42<01:37, 31.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12235/15290 [05:42<01:41, 29.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12239/15290 [05:42<01:41, 30.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12243/15290 [05:42<01:44, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12246/15290 [05:42<01:46, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12249/15290 [05:42<01:46, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12252/15290 [05:43<01:47, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12255/15290 [05:43<01:45, 28.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12258/15290 [05:43<01:45, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12261/15290 [05:43<01:47, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12264/15290 [05:43<01:49, 27.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12267/15290 [05:43<01:49, 27.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12270/15290 [05:43<01:49, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12273/15290 [05:43<01:48, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12276/15290 [05:43<01:47, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12280/15290 [05:44<01:44, 28.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12284/15290 [05:44<01:42, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12287/15290 [05:44<01:41, 29.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12290/15290 [05:44<01:41, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12294/15290 [05:44<01:40, 29.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12297/15290 [05:44<01:40, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12301/15290 [05:44<01:37, 30.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12305/15290 [05:44<01:38, 30.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12309/15290 [05:44<01:43, 28.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12312/15290 [05:45<01:45, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12315/15290 [05:45<01:44, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12318/15290 [05:45<01:44, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12321/15290 [05:45<01:43, 28.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12325/15290 [05:45<01:39, 29.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12328/15290 [05:45<01:40, 29.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12332/15290 [05:45<01:37, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12336/15290 [05:45<01:38, 29.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12340/15290 [05:46<01:36, 30.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12344/15290 [05:46<01:36, 30.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12348/15290 [05:46<01:35, 30.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12352/15290 [05:46<01:33, 31.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12356/15290 [05:46<01:37, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12360/15290 [05:46<01:38, 29.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12363/15290 [05:46<01:38, 29.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12367/15290 [05:46<01:38, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12370/15290 [05:47<01:40, 28.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12374/15290 [05:47<01:38, 29.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12377/15290 [05:47<01:39, 29.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12381/15290 [05:47<01:35, 30.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12385/15290 [05:47<01:36, 30.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12389/15290 [05:48<03:27, 13.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12392/15290 [05:48<03:04, 15.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12395/15290 [05:48<02:42, 17.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12399/15290 [05:48<02:17, 21.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12403/15290 [05:48<02:03, 23.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12407/15290 [05:48<01:50, 26.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12411/15290 [05:48<01:44, 27.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12415/15290 [05:49<01:39, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12419/15290 [05:49<01:36, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12423/15290 [05:49<01:33, 30.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12427/15290 [05:49<01:29, 31.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12431/15290 [05:49<01:28, 32.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12435/15290 [05:49<01:28, 32.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12439/15290 [05:49<01:27, 32.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12443/15290 [05:49<01:25, 33.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12447/15290 [05:49<01:24, 33.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12451/15290 [05:50<01:24, 33.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12455/15290 [05:50<01:23, 33.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12459/15290 [05:50<01:24, 33.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12463/15290 [05:50<01:24, 33.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12467/15290 [05:50<01:24, 33.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12471/15290 [05:50<01:23, 33.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12475/15290 [05:50<01:24, 33.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12479/15290 [05:50<01:28, 31.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12483/15290 [05:51<01:28, 31.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12487/15290 [05:51<01:33, 30.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12491/15290 [05:51<01:39, 28.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12495/15290 [05:51<01:35, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12498/15290 [05:51<01:40, 27.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12501/15290 [05:51<01:40, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12505/15290 [05:51<01:34, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12508/15290 [05:51<01:35, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12511/15290 [05:52<01:38, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12515/15290 [05:52<01:33, 29.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12518/15290 [05:52<01:40, 27.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12521/15290 [05:52<01:39, 27.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12525/15290 [05:52<01:36, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12528/15290 [05:52<01:38, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12531/15290 [05:52<01:41, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12534/15290 [05:52<01:39, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12537/15290 [05:53<01:44, 26.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12540/15290 [05:53<01:45, 26.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12543/15290 [05:53<01:44, 26.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12546/15290 [05:53<01:45, 26.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12550/15290 [05:53<01:37, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12554/15290 [05:53<01:30, 30.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12558/15290 [05:53<01:30, 30.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12562/15290 [05:53<01:36, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12566/15290 [05:54<01:32, 29.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12569/15290 [05:54<01:33, 29.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12573/15290 [05:54<01:31, 29.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12577/15290 [05:54<01:28, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12581/15290 [05:54<01:25, 31.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12585/15290 [05:54<01:25, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12589/15290 [05:54<01:25, 31.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12593/15290 [05:54<01:26, 31.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12597/15290 [05:55<01:32, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12600/15290 [05:55<01:34, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12603/15290 [05:55<01:33, 28.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12607/15290 [05:55<01:29, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12611/15290 [05:55<01:25, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12615/15290 [05:55<01:26, 30.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12619/15290 [05:55<01:25, 31.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12623/15290 [05:55<01:26, 30.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12627/15290 [05:56<01:25, 31.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12631/15290 [05:56<01:25, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12635/15290 [05:56<01:24, 31.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12639/15290 [05:56<01:22, 32.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12643/15290 [05:56<01:21, 32.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12647/15290 [05:56<01:24, 31.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12651/15290 [05:56<01:22, 32.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12655/15290 [05:56<01:22, 32.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12659/15290 [05:57<01:25, 30.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12663/15290 [05:57<01:27, 29.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12667/15290 [05:57<01:35, 27.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12670/15290 [05:57<01:33, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12673/15290 [05:57<01:32, 28.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12677/15290 [05:57<01:26, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12681/15290 [05:57<01:24, 31.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12685/15290 [05:57<01:20, 32.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12689/15290 [05:58<01:21, 32.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12693/15290 [05:58<01:19, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12697/15290 [05:58<01:23, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12701/15290 [05:58<01:25, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12705/15290 [05:58<01:25, 30.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12709/15290 [05:58<01:26, 29.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12712/15290 [05:58<01:27, 29.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12715/15290 [05:58<01:28, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12718/15290 [05:59<01:30, 28.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12721/15290 [05:59<01:30, 28.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12724/15290 [05:59<01:30, 28.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12727/15290 [05:59<01:28, 28.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12730/15290 [05:59<01:29, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12733/15290 [05:59<01:28, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12737/15290 [05:59<01:28, 28.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12740/15290 [05:59<01:33, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12743/15290 [05:59<01:31, 27.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12746/15290 [06:00<01:30, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12750/15290 [06:00<01:27, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12753/15290 [06:00<01:28, 28.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12756/15290 [06:00<01:31, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12759/15290 [06:00<01:33, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12762/15290 [06:00<01:31, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12766/15290 [06:00<01:27, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12769/15290 [06:00<01:27, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12773/15290 [06:00<01:25, 29.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12776/15290 [06:01<01:25, 29.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12779/15290 [06:01<01:26, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12782/15290 [06:01<01:26, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12785/15290 [06:01<01:26, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12789/15290 [06:01<01:22, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12793/15290 [06:01<01:24, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12797/15290 [06:01<01:23, 29.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12800/15290 [06:01<01:24, 29.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12804/15290 [06:01<01:21, 30.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12808/15290 [06:02<01:23, 29.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12811/15290 [06:02<01:24, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12814/15290 [06:02<01:26, 28.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12817/15290 [06:02<01:25, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12820/15290 [06:02<01:26, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12823/15290 [06:02<01:26, 28.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12826/15290 [06:02<01:26, 28.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12829/15290 [06:02<01:27, 28.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12832/15290 [06:02<01:26, 28.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12835/15290 [06:03<01:25, 28.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12838/15290 [06:03<01:26, 28.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12841/15290 [06:03<01:27, 28.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12844/15290 [06:03<01:30, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12847/15290 [06:03<01:28, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12850/15290 [06:03<01:26, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12854/15290 [06:03<01:20, 30.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12858/15290 [06:03<01:20, 30.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12862/15290 [06:03<01:18, 31.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12866/15290 [06:04<01:17, 31.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12870/15290 [06:04<01:19, 30.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12874/15290 [06:04<01:23, 29.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12877/15290 [06:04<01:26, 27.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12881/15290 [06:04<01:23, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12885/15290 [06:04<01:20, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12889/15290 [06:04<01:18, 30.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12893/15290 [06:05<01:20, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12896/15290 [06:05<01:21, 29.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12899/15290 [06:05<01:24, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12903/15290 [06:05<01:20, 29.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12906/15290 [06:05<01:23, 28.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12909/15290 [06:05<01:22, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12913/15290 [06:05<01:18, 30.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12917/15290 [06:05<01:15, 31.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12921/15290 [06:05<01:14, 31.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12925/15290 [06:06<01:21, 28.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12929/15290 [06:06<01:18, 29.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12933/15290 [06:06<01:15, 31.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12937/15290 [06:06<01:13, 32.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12941/15290 [06:06<01:13, 32.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12945/15290 [06:06<01:15, 31.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12949/15290 [06:06<01:14, 31.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12953/15290 [06:07<01:17, 30.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12957/15290 [06:07<01:19, 29.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12960/15290 [06:07<01:19, 29.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12964/15290 [06:07<01:18, 29.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12967/15290 [06:07<01:20, 28.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12971/15290 [06:07<01:18, 29.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12975/15290 [06:07<01:14, 30.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12979/15290 [06:07<01:15, 30.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12983/15290 [06:08<01:13, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12987/15290 [06:08<01:13, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12991/15290 [06:08<01:13, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12995/15290 [06:08<01:12, 31.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 12999/15290 [06:08<01:15, 30.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13003/15290 [06:08<01:14, 30.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13007/15290 [06:08<01:13, 31.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13011/15290 [06:08<01:13, 30.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13015/15290 [06:09<01:14, 30.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13019/15290 [06:09<01:14, 30.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13023/15290 [06:09<01:16, 29.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13026/15290 [06:09<01:16, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13029/15290 [06:09<01:16, 29.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13032/15290 [06:09<01:20, 28.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13035/15290 [06:09<01:18, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13038/15290 [06:09<01:17, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13041/15290 [06:09<01:17, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13045/15290 [06:10<01:13, 30.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13049/15290 [06:10<01:12, 30.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13053/15290 [06:10<01:13, 30.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13057/15290 [06:10<01:12, 30.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13061/15290 [06:10<01:14, 30.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13065/15290 [06:10<01:13, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13069/15290 [06:10<01:12, 30.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13073/15290 [06:10<01:12, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13077/15290 [06:11<01:12, 30.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13081/15290 [06:11<01:12, 30.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13085/15290 [06:11<01:11, 30.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13089/15290 [06:11<01:11, 30.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13093/15290 [06:11<01:10, 31.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13097/15290 [06:11<01:10, 31.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13101/15290 [06:11<01:11, 30.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13105/15290 [06:12<01:11, 30.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13109/15290 [06:12<01:11, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13113/15290 [06:12<01:11, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13117/15290 [06:12<01:11, 30.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13121/15290 [06:12<01:12, 30.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13125/15290 [06:12<01:15, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13128/15290 [06:12<01:15, 28.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13131/15290 [06:12<01:14, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13134/15290 [06:13<01:14, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13137/15290 [06:13<01:13, 29.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13140/15290 [06:13<01:13, 29.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13143/15290 [06:13<01:13, 29.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13146/15290 [06:13<01:12, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13150/15290 [06:13<01:10, 30.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13154/15290 [06:13<01:17, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13158/15290 [06:13<01:14, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13162/15290 [06:13<01:11, 29.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13166/15290 [06:14<01:09, 30.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13170/15290 [06:14<01:14, 28.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13173/15290 [06:14<01:15, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13176/15290 [06:14<01:14, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13180/15290 [06:14<01:11, 29.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13183/15290 [06:14<01:11, 29.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13187/15290 [06:14<01:09, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13191/15290 [06:14<01:09, 30.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13195/15290 [06:15<01:10, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13199/15290 [06:15<01:10, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13202/15290 [06:15<01:10, 29.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13206/15290 [06:15<01:10, 29.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13209/15290 [06:15<01:12, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13212/15290 [06:15<01:13, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13215/15290 [06:15<01:14, 27.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13218/15290 [06:15<01:13, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13221/15290 [06:16<01:14, 27.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13224/15290 [06:16<01:13, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13227/15290 [06:16<01:14, 27.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13231/15290 [06:16<01:10, 29.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13235/15290 [06:16<01:08, 29.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13238/15290 [06:16<01:09, 29.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13241/15290 [06:16<01:09, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13245/15290 [06:16<01:07, 30.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13249/15290 [06:16<01:06, 30.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13253/15290 [06:17<01:05, 30.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13257/15290 [06:17<01:06, 30.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13261/15290 [06:17<01:07, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13265/15290 [06:17<01:07, 29.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13268/15290 [06:17<01:10, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13271/15290 [06:17<01:13, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13275/15290 [06:17<01:09, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13279/15290 [06:17<01:07, 29.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13283/15290 [06:18<01:04, 30.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13287/15290 [06:18<01:06, 30.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13291/15290 [06:18<01:06, 30.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13295/15290 [06:18<01:09, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13298/15290 [06:18<01:11, 27.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13301/15290 [06:18<01:12, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13304/15290 [06:18<01:13, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13307/15290 [06:19<01:18, 25.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13310/15290 [06:19<01:17, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13313/15290 [06:19<01:15, 26.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13316/15290 [06:19<01:12, 27.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13320/15290 [06:19<01:08, 28.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13324/15290 [06:19<01:07, 29.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13327/15290 [06:19<01:08, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13330/15290 [06:19<01:13, 26.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13333/15290 [06:19<01:13, 26.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13336/15290 [06:20<01:13, 26.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13339/15290 [06:20<01:14, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13342/15290 [06:20<01:16, 25.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13345/15290 [06:20<01:15, 25.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13348/15290 [06:20<01:12, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13351/15290 [06:20<01:11, 27.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13355/15290 [06:20<01:08, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13359/15290 [06:20<01:05, 29.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13362/15290 [06:20<01:05, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13365/15290 [06:21<01:05, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13369/15290 [06:21<01:04, 29.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13373/15290 [06:21<01:03, 30.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13377/15290 [06:21<01:02, 30.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13381/15290 [06:21<01:09, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13384/15290 [06:21<01:09, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13388/15290 [06:21<01:06, 28.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13391/15290 [06:22<01:06, 28.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13395/15290 [06:22<01:04, 29.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13399/15290 [06:22<01:03, 29.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13403/15290 [06:22<01:01, 30.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13407/15290 [06:22<01:04, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13410/15290 [06:22<01:04, 29.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13413/15290 [06:22<01:06, 28.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13416/15290 [06:22<01:10, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13420/15290 [06:22<01:05, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13423/15290 [06:23<01:05, 28.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13426/15290 [06:23<01:09, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13429/15290 [06:23<01:07, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13432/15290 [06:23<01:07, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13435/15290 [06:23<01:07, 27.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13439/15290 [06:23<01:02, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13442/15290 [06:23<01:02, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13446/15290 [06:23<00:58, 31.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13450/15290 [06:24<00:57, 32.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13454/15290 [06:24<00:56, 32.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13458/15290 [06:24<00:56, 32.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13462/15290 [06:24<00:55, 32.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13466/15290 [06:24<00:55, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13470/15290 [06:24<00:55, 32.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13474/15290 [06:24<00:56, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13478/15290 [06:24<00:56, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13482/15290 [06:24<00:56, 32.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13486/15290 [06:25<00:58, 31.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13490/15290 [06:25<01:02, 28.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13494/15290 [06:25<01:00, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13498/15290 [06:25<00:59, 30.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13502/15290 [06:25<01:00, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13506/15290 [06:25<01:01, 29.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13509/15290 [06:25<01:04, 27.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13512/15290 [06:26<01:04, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13516/15290 [06:26<01:01, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13520/15290 [06:26<01:00, 29.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13523/15290 [06:26<00:59, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13527/15290 [06:26<00:58, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13531/15290 [06:26<00:58, 30.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13535/15290 [06:26<00:57, 30.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13539/15290 [06:26<00:56, 30.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13543/15290 [06:27<00:57, 30.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13547/15290 [06:27<00:58, 29.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13550/15290 [06:27<00:59, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13553/15290 [06:27<01:00, 28.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13556/15290 [06:27<00:59, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13559/15290 [06:27<00:58, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13562/15290 [06:27<00:58, 29.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13566/15290 [06:27<00:57, 29.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13570/15290 [06:27<00:57, 30.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13574/15290 [06:28<00:55, 30.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13578/15290 [06:28<01:13, 23.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13582/15290 [06:28<01:07, 25.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13586/15290 [06:28<01:02, 27.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13590/15290 [06:28<01:00, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13593/15290 [06:28<00:59, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13597/15290 [06:28<00:57, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13601/15290 [06:29<00:55, 30.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13605/15290 [06:29<00:54, 30.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13609/15290 [06:29<00:53, 31.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13613/15290 [06:29<00:53, 31.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13617/15290 [06:29<00:53, 31.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13621/15290 [06:29<00:54, 30.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13625/15290 [06:29<00:54, 30.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13629/15290 [06:29<00:53, 31.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13633/15290 [06:30<00:53, 30.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13637/15290 [06:30<00:56, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13640/15290 [06:30<00:56, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13644/15290 [06:30<00:55, 29.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13647/15290 [06:30<00:55, 29.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13650/15290 [06:30<00:55, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13653/15290 [06:30<00:57, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13656/15290 [06:30<00:56, 28.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13659/15290 [06:31<00:55, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13662/15290 [06:31<00:57, 28.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13665/15290 [06:31<00:58, 27.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13668/15290 [06:31<00:58, 27.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13671/15290 [06:31<00:59, 27.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13674/15290 [06:31<01:01, 26.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13677/15290 [06:31<01:02, 25.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13680/15290 [06:31<01:01, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13683/15290 [06:31<01:00, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13686/15290 [06:32<00:59, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13689/15290 [06:32<00:58, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13692/15290 [06:32<00:57, 27.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13695/15290 [06:32<00:56, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13698/15290 [06:32<00:57, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13701/15290 [06:32<00:59, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13704/15290 [06:32<00:59, 26.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13707/15290 [06:32<00:58, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13710/15290 [06:32<00:57, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13713/15290 [06:33<00:56, 28.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13716/15290 [06:33<00:59, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13719/15290 [06:33<01:06, 23.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13722/15290 [06:33<01:07, 23.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13725/15290 [06:33<01:11, 21.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13728/15290 [06:33<01:06, 23.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13731/15290 [06:33<01:04, 24.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13734/15290 [06:33<01:03, 24.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13737/15290 [06:34<01:01, 25.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13740/15290 [06:34<01:01, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13743/15290 [06:34<00:59, 26.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13746/15290 [06:34<00:58, 26.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13749/15290 [06:34<00:57, 26.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13752/15290 [06:34<00:55, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13755/15290 [06:34<00:55, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13759/15290 [06:34<00:52, 29.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13762/15290 [06:34<00:52, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13765/15290 [06:35<00:52, 28.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13768/15290 [06:35<00:52, 28.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13771/15290 [06:35<00:54, 27.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13774/15290 [06:35<00:54, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13777/15290 [06:35<00:53, 28.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13780/15290 [06:35<00:55, 27.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13783/15290 [06:35<01:07, 22.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13786/15290 [06:35<01:08, 22.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13789/15290 [06:36<01:03, 23.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13792/15290 [06:36<01:00, 24.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13795/15290 [06:36<00:58, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13798/15290 [06:36<00:56, 26.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13801/15290 [06:36<00:57, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13804/15290 [06:36<00:56, 26.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13807/15290 [06:36<00:58, 25.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13810/15290 [06:36<00:57, 25.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13813/15290 [06:36<00:55, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13817/15290 [06:37<00:51, 28.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13820/15290 [06:37<00:50, 29.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13824/15290 [06:37<00:49, 29.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13827/15290 [06:37<00:49, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13830/15290 [06:37<00:49, 29.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13834/15290 [06:37<00:48, 30.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13838/15290 [06:37<00:49, 29.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13841/15290 [06:37<00:49, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13845/15290 [06:37<00:48, 29.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13849/15290 [06:38<00:47, 30.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13853/15290 [06:38<00:47, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13857/15290 [06:38<00:48, 29.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13861/15290 [06:38<00:49, 29.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13864/15290 [06:38<00:49, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13867/15290 [06:38<00:49, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13870/15290 [06:38<00:49, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13873/15290 [06:38<00:52, 27.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13876/15290 [06:39<00:51, 27.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13879/15290 [06:39<00:50, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13882/15290 [06:39<00:51, 27.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13885/15290 [06:39<00:52, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13888/15290 [06:39<00:54, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13891/15290 [06:39<00:56, 24.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13894/15290 [06:39<00:56, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13897/15290 [06:39<00:54, 25.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13900/15290 [06:40<00:53, 26.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13904/15290 [06:40<00:49, 27.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13907/15290 [06:40<00:48, 28.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13911/15290 [06:40<00:45, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13915/15290 [06:40<00:44, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13919/15290 [06:40<00:45, 29.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13923/15290 [06:40<00:45, 29.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13926/15290 [06:40<00:46, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13929/15290 [06:41<00:49, 27.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13932/15290 [06:41<00:48, 27.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13935/15290 [06:41<00:47, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13938/15290 [06:41<00:49, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13941/15290 [06:41<00:49, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13944/15290 [06:41<00:49, 27.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13947/15290 [06:41<00:49, 26.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13950/15290 [06:41<00:48, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13954/15290 [06:41<00:46, 28.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13958/15290 [06:42<00:45, 29.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13961/15290 [06:42<00:45, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13965/15290 [06:42<00:45, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13969/15290 [06:42<00:44, 29.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13972/15290 [06:42<00:45, 29.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13976/15290 [06:42<00:44, 29.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13979/15290 [06:42<00:44, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13982/15290 [06:42<00:44, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13986/15290 [06:42<00:42, 30.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13990/15290 [06:43<00:42, 30.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 13994/15290 [06:43<00:41, 31.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 13998/15290 [06:43<00:41, 31.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14002/15290 [06:43<00:40, 31.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14006/15290 [06:43<00:40, 32.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14010/15290 [06:43<00:39, 32.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14014/15290 [06:43<00:40, 31.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14018/15290 [06:43<00:39, 31.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14022/15290 [06:44<00:42, 29.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14026/15290 [06:44<00:44, 28.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14029/15290 [06:44<00:45, 27.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14032/15290 [06:44<00:45, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14035/15290 [06:44<00:46, 27.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14038/15290 [06:44<00:45, 27.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14041/15290 [06:44<00:44, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14044/15290 [06:44<00:44, 27.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14047/15290 [06:45<00:46, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14050/15290 [06:45<00:47, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14053/15290 [06:45<00:45, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14056/15290 [06:45<00:45, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14060/15290 [06:45<00:46, 26.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14063/15290 [06:45<00:56, 21.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14066/15290 [06:45<01:04, 18.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14069/15290 [06:46<01:01, 19.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14072/15290 [06:46<00:56, 21.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14075/15290 [06:46<00:52, 23.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14078/15290 [06:46<00:48, 24.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14082/15290 [06:46<00:44, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14085/15290 [06:46<00:44, 27.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14088/15290 [06:46<00:44, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14091/15290 [06:46<00:42, 27.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14094/15290 [06:46<00:42, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14097/15290 [06:47<00:42, 27.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14100/15290 [06:47<00:41, 28.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14103/15290 [06:47<00:42, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14106/15290 [06:47<00:41, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14109/15290 [06:47<00:41, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14113/15290 [06:47<00:40, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14116/15290 [06:47<00:41, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14119/15290 [06:47<00:40, 28.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14122/15290 [06:47<00:41, 28.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14125/15290 [06:48<00:41, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14128/15290 [06:48<00:41, 27.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14131/15290 [06:48<00:42, 27.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14134/15290 [06:48<00:42, 26.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14137/15290 [06:48<00:41, 27.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14140/15290 [06:48<00:41, 27.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14144/15290 [06:48<00:39, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14147/15290 [06:48<00:39, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14150/15290 [06:48<00:41, 27.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14153/15290 [06:49<00:43, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14156/15290 [06:49<00:43, 25.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14159/15290 [06:49<00:45, 24.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14162/15290 [06:49<00:43, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14165/15290 [06:49<00:42, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14168/15290 [06:49<00:42, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14171/15290 [06:49<00:41, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14174/15290 [06:49<00:42, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14177/15290 [06:49<00:42, 26.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14180/15290 [06:50<00:43, 25.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14183/15290 [06:50<00:44, 24.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14186/15290 [06:50<00:44, 24.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14189/15290 [06:50<00:43, 25.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14192/15290 [06:50<00:43, 25.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14196/15290 [06:50<00:40, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14199/15290 [06:50<00:39, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14203/15290 [06:50<00:37, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14206/15290 [06:51<00:38, 28.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14210/15290 [06:51<00:36, 29.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14213/15290 [06:51<00:36, 29.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14216/15290 [06:51<00:36, 29.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14219/15290 [06:51<00:37, 28.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14222/15290 [06:51<00:39, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14225/15290 [06:51<00:40, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14228/15290 [06:51<00:39, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14231/15290 [06:51<00:38, 27.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14234/15290 [06:52<00:38, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14237/15290 [06:52<00:37, 27.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14240/15290 [06:52<00:38, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14243/15290 [06:52<00:38, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14246/15290 [06:52<00:39, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14249/15290 [06:52<00:38, 27.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14252/15290 [06:52<00:37, 27.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14256/15290 [06:52<00:35, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14260/15290 [06:52<00:34, 29.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14264/15290 [06:53<00:33, 30.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14268/15290 [06:53<00:33, 30.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14272/15290 [06:53<00:35, 28.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14275/15290 [06:53<00:36, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14278/15290 [06:53<00:35, 28.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14281/15290 [06:53<00:35, 28.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14284/15290 [06:53<00:34, 28.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14287/15290 [06:53<00:34, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14291/15290 [06:54<00:33, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14295/15290 [06:54<00:32, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14299/15290 [06:54<00:32, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14303/15290 [06:54<00:32, 30.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14307/15290 [06:54<00:33, 29.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14310/15290 [06:54<00:34, 28.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14313/15290 [06:54<00:37, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14316/15290 [06:54<00:36, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14319/15290 [06:55<00:35, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14323/15290 [06:55<00:33, 28.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14327/15290 [06:55<00:32, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14330/15290 [06:55<00:33, 28.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14333/15290 [06:55<00:33, 28.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14336/15290 [06:55<00:33, 28.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14340/15290 [06:55<00:33, 28.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14344/15290 [06:55<00:32, 29.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14347/15290 [06:56<00:31, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14351/15290 [06:56<00:31, 29.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14354/15290 [06:56<00:31, 29.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14357/15290 [06:56<00:31, 29.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14360/15290 [06:56<00:31, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14364/15290 [06:56<00:30, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14367/15290 [06:56<00:30, 29.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14371/15290 [06:56<00:30, 30.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14375/15290 [06:56<00:30, 29.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14378/15290 [06:57<00:31, 29.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14381/15290 [06:57<00:36, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14384/15290 [06:57<00:36, 24.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14387/15290 [06:57<00:36, 24.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14390/15290 [06:57<00:37, 23.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14393/15290 [06:57<00:36, 24.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14397/15290 [06:57<00:33, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14401/15290 [06:57<00:31, 28.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14405/15290 [06:58<00:30, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14408/15290 [06:58<00:30, 28.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14411/15290 [06:58<00:30, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14414/15290 [06:58<00:31, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14417/15290 [06:58<00:30, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14421/15290 [06:58<00:29, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14424/15290 [06:58<00:29, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14428/15290 [06:58<00:28, 30.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14432/15290 [06:59<00:28, 29.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14435/15290 [06:59<00:28, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14439/15290 [06:59<00:28, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14442/15290 [06:59<00:29, 28.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14445/15290 [06:59<00:29, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14448/15290 [06:59<00:30, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14451/15290 [06:59<00:29, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14454/15290 [06:59<00:29, 28.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14457/15290 [06:59<00:30, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14460/15290 [07:00<00:29, 27.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14463/15290 [07:00<00:29, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14466/15290 [07:00<00:29, 28.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14469/15290 [07:00<00:29, 27.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14472/15290 [07:00<00:31, 25.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14475/15290 [07:00<00:33, 24.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14478/15290 [07:00<00:32, 25.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14481/15290 [07:00<00:31, 25.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14484/15290 [07:00<00:31, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14487/15290 [07:01<00:30, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14490/15290 [07:01<00:30, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14494/15290 [07:01<00:28, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14498/15290 [07:01<00:27, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14501/15290 [07:01<00:28, 27.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14504/15290 [07:01<00:27, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14508/15290 [07:01<00:26, 29.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14511/15290 [07:01<00:27, 28.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14514/15290 [07:01<00:27, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14517/15290 [07:02<00:26, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14520/15290 [07:02<00:26, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14523/15290 [07:02<00:27, 27.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14526/15290 [07:02<00:27, 27.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14529/15290 [07:02<00:27, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14532/15290 [07:02<00:27, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14535/15290 [07:02<00:26, 28.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14538/15290 [07:02<00:26, 28.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14541/15290 [07:02<00:26, 28.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14544/15290 [07:03<00:28, 26.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14547/15290 [07:03<00:28, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14550/15290 [07:03<00:29, 24.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14553/15290 [07:03<00:30, 24.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14556/15290 [07:03<00:30, 24.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14559/15290 [07:03<00:29, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14562/15290 [07:03<00:28, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14565/15290 [07:03<00:27, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14568/15290 [07:04<00:27, 26.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14571/15290 [07:04<00:27, 26.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14574/15290 [07:04<00:26, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14577/15290 [07:04<00:26, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14580/15290 [07:04<00:26, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14583/15290 [07:04<00:25, 27.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14586/15290 [07:04<00:25, 27.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14589/15290 [07:04<00:25, 27.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14592/15290 [07:04<00:25, 27.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14595/15290 [07:05<00:28, 24.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14598/15290 [07:05<00:29, 23.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14601/15290 [07:05<00:29, 23.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14604/15290 [07:05<00:27, 25.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14607/15290 [07:05<00:26, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14611/15290 [07:05<00:24, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14614/15290 [07:05<00:24, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14618/15290 [07:05<00:23, 28.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14621/15290 [07:05<00:23, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14624/15290 [07:06<00:24, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14627/15290 [07:06<00:25, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14630/15290 [07:06<00:25, 25.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14633/15290 [07:06<00:24, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14637/15290 [07:06<00:23, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14640/15290 [07:06<00:23, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14643/15290 [07:06<00:23, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14647/15290 [07:06<00:22, 28.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14650/15290 [07:07<00:22, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14654/15290 [07:07<00:21, 30.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14658/15290 [07:07<00:21, 29.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14661/15290 [07:07<00:21, 29.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14664/15290 [07:07<00:21, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14667/15290 [07:07<00:21, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14671/15290 [07:07<00:20, 29.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14674/15290 [07:07<00:21, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14677/15290 [07:07<00:21, 28.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14680/15290 [07:08<00:21, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14683/15290 [07:08<00:21, 27.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14686/15290 [07:08<00:21, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14689/15290 [07:08<00:21, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14693/15290 [07:08<00:20, 28.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14697/15290 [07:08<00:20, 29.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14700/15290 [07:08<00:20, 29.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14704/15290 [07:08<00:19, 29.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14707/15290 [07:09<00:20, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14710/15290 [07:09<00:20, 28.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14713/15290 [07:09<00:20, 28.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14716/15290 [07:09<00:19, 28.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14719/15290 [07:09<00:19, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14723/15290 [07:09<00:19, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14727/15290 [07:09<00:18, 29.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14730/15290 [07:09<00:19, 29.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14733/15290 [07:09<00:19, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14736/15290 [07:10<00:19, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14740/15290 [07:10<00:18, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14744/15290 [07:10<00:18, 29.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14747/15290 [07:10<00:18, 29.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14751/15290 [07:10<00:17, 30.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14754/15290 [07:10<00:18, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14758/15290 [07:10<00:17, 29.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14761/15290 [07:10<00:17, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14764/15290 [07:10<00:17, 29.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14767/15290 [07:11<00:18, 28.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14770/15290 [07:11<00:18, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14773/15290 [07:11<00:18, 27.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14776/15290 [07:11<00:18, 27.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14779/15290 [07:11<00:18, 27.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14782/15290 [07:11<00:18, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14785/15290 [07:11<00:18, 27.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14788/15290 [07:11<00:18, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14791/15290 [07:11<00:18, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14794/15290 [07:12<00:18, 27.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14797/15290 [07:12<00:17, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14800/15290 [07:12<00:17, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14803/15290 [07:12<00:17, 27.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14806/15290 [07:12<00:17, 27.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14809/15290 [07:12<00:17, 27.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14812/15290 [07:12<00:17, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14815/15290 [07:12<00:17, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14818/15290 [07:12<00:17, 26.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14821/15290 [07:13<00:17, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14824/15290 [07:13<00:17, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14827/15290 [07:13<00:16, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14830/15290 [07:13<00:16, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14833/15290 [07:13<00:17, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14836/15290 [07:13<00:16, 27.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14839/15290 [07:13<00:16, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14842/15290 [07:13<00:16, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14846/15290 [07:13<00:15, 28.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14849/15290 [07:14<00:15, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14852/15290 [07:14<00:15, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14855/15290 [07:14<00:15, 27.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14859/15290 [07:14<00:15, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14862/15290 [07:14<00:15, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14866/15290 [07:14<00:14, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14869/15290 [07:14<00:14, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14872/15290 [07:14<00:14, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14875/15290 [07:14<00:14, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14878/15290 [07:15<00:14, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14881/15290 [07:15<00:14, 28.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14884/15290 [07:15<00:14, 28.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14887/15290 [07:15<00:15, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14890/15290 [07:15<00:15, 25.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14893/15290 [07:15<00:15, 26.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14896/15290 [07:15<00:15, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14899/15290 [07:15<00:14, 26.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14902/15290 [07:16<00:15, 25.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14905/15290 [07:16<00:14, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14908/15290 [07:16<00:14, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14911/15290 [07:16<00:14, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14914/15290 [07:16<00:14, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14917/15290 [07:16<00:14, 25.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14920/15290 [07:16<00:14, 26.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14923/15290 [07:16<00:13, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14926/15290 [07:16<00:13, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14929/15290 [07:17<00:13, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14932/15290 [07:17<00:12, 27.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14935/15290 [07:17<00:13, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14938/15290 [07:17<00:13, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14942/15290 [07:17<00:12, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14945/15290 [07:17<00:12, 28.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14949/15290 [07:17<00:11, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14952/15290 [07:17<00:11, 29.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14955/15290 [07:17<00:11, 29.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14958/15290 [07:18<00:11, 29.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14961/15290 [07:18<00:11, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14964/15290 [07:18<00:11, 27.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14967/15290 [07:18<00:12, 26.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14971/15290 [07:18<00:11, 28.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14974/15290 [07:18<00:11, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14977/15290 [07:18<00:10, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14980/15290 [07:18<00:10, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14983/15290 [07:18<00:10, 28.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14986/15290 [07:19<00:10, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14989/15290 [07:19<00:10, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14992/15290 [07:19<00:10, 28.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14995/15290 [07:19<00:10, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14998/15290 [07:19<00:10, 28.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15001/15290 [07:19<00:10, 28.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15004/15290 [07:19<00:10, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15007/15290 [07:19<00:10, 28.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15010/15290 [07:19<00:09, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15013/15290 [07:19<00:10, 27.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15016/15290 [07:20<00:10, 27.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15019/15290 [07:20<00:09, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15022/15290 [07:20<00:10, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15025/15290 [07:20<00:10, 25.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15028/15290 [07:20<00:10, 25.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15031/15290 [07:20<00:10, 25.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15034/15290 [07:20<00:09, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15037/15290 [07:20<00:09, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15040/15290 [07:21<00:09, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15043/15290 [07:21<00:09, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15046/15290 [07:21<00:09, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15049/15290 [07:21<00:09, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15052/15290 [07:21<00:09, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15055/15290 [07:21<00:09, 24.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15058/15290 [07:21<00:09, 24.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15061/15290 [07:21<00:08, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15065/15290 [07:21<00:08, 27.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15068/15290 [07:22<00:07, 27.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15071/15290 [07:22<00:08, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15074/15290 [07:22<00:08, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15077/15290 [07:22<00:08, 26.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15080/15290 [07:22<00:07, 26.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15083/15290 [07:22<00:07, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15086/15290 [07:22<00:07, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15089/15290 [07:22<00:07, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15092/15290 [07:23<00:07, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15095/15290 [07:23<00:07, 25.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15098/15290 [07:23<00:07, 25.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15101/15290 [07:23<00:07, 26.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15104/15290 [07:23<00:06, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15107/15290 [07:23<00:07, 25.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15110/15290 [07:23<00:07, 25.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15113/15290 [07:23<00:06, 25.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15116/15290 [07:23<00:06, 25.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15119/15290 [07:24<00:06, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15122/15290 [07:24<00:06, 24.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15125/15290 [07:24<00:07, 23.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15128/15290 [07:24<00:06, 24.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15131/15290 [07:24<00:06, 25.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15134/15290 [07:24<00:05, 26.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15137/15290 [07:24<00:05, 26.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15140/15290 [07:24<00:05, 26.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15143/15290 [07:24<00:05, 27.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15146/15290 [07:25<00:05, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15149/15290 [07:25<00:04, 28.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15152/15290 [07:25<00:05, 27.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15155/15290 [07:25<00:05, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15158/15290 [07:25<00:05, 26.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15161/15290 [07:25<00:04, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15164/15290 [07:25<00:04, 26.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15167/15290 [07:25<00:04, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15170/15290 [07:25<00:04, 27.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15173/15290 [07:26<00:04, 27.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15176/15290 [07:26<00:04, 27.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15179/15290 [07:26<00:04, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15182/15290 [07:26<00:04, 26.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15185/15290 [07:26<00:03, 26.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15188/15290 [07:26<00:03, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15191/15290 [07:26<00:03, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15195/15290 [07:26<00:03, 27.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15198/15290 [07:27<00:03, 27.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15201/15290 [07:27<00:03, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15204/15290 [07:27<00:03, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15207/15290 [07:27<00:03, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15210/15290 [07:27<00:02, 27.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15213/15290 [07:27<00:02, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15216/15290 [07:27<00:02, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15219/15290 [07:27<00:02, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15222/15290 [07:27<00:02, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15225/15290 [07:28<00:02, 27.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15228/15290 [07:28<00:02, 27.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15231/15290 [07:28<00:02, 26.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15235/15290 [07:28<00:01, 28.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15238/15290 [07:28<00:01, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15241/15290 [07:28<00:01, 27.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15244/15290 [07:28<00:01, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15247/15290 [07:28<00:01, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15250/15290 [07:28<00:01, 26.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15254/15290 [07:29<00:01, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15257/15290 [07:29<00:01, 27.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15260/15290 [07:29<00:01, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15263/15290 [07:29<00:00, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15267/15290 [07:29<00:00, 29.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15270/15290 [07:29<00:00, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15273/15290 [07:29<00:00, 27.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15276/15290 [07:29<00:00, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15279/15290 [07:29<00:00, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15282/15290 [07:30<00:00, 27.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15285/15290 [07:30<00:00, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15288/15290 [07:30<00:00, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:6: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_post_nlp[master_key] = np.vectorize(create_score_column,otypes = [float])(df_post_nlp['dict'],master_key,df_post_nlp['word_count'],score_type,0,idf_all,idf_word)
100%|██████████| 15290/15290 [07:30<00:00, 33.95it/s]

Scoring target set:

  1%|          | 94/15290 [00:02<06:18, 40.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 99/15290 [00:02<06:18, 40.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 104/15290 [00:02<06:30, 38.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 108/15290 [00:02<06:43, 37.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 112/15290 [00:02<06:53, 36.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 116/15290 [00:03<08:18, 30.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 120/15290 [00:03<07:46, 32.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 125/15290 [00:03<07:17, 34.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 129/15290 [00:03<07:04, 35.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 134/15290 [00:03<06:40, 37.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 138/15290 [00:03<06:49, 37.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 142/15290 [00:03<06:54, 36.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 146/15290 [00:03<07:08, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 150/15290 [00:04<07:00, 36.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 155/15290 [00:04<06:32, 38.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 160/15290 [00:04<06:22, 39.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 165/15290 [00:04<06:13, 40.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 170/15290 [00:04<06:12, 40.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 175/15290 [00:04<06:19, 39.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 179/15290 [00:04<06:20, 39.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 183/15290 [00:04<06:20, 39.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|          | 187/15290 [00:04<06:23, 39.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 192/15290 [00:05<06:15, 40.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 197/15290 [00:05<06:23, 39.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 202/15290 [00:05<06:18, 39.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 206/15290 [00:05<06:26, 39.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 210/15290 [00:05<06:27, 38.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 215/15290 [00:05<06:22, 39.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 219/15290 [00:05<06:31, 38.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 224/15290 [00:05<06:26, 38.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  1%|▏         | 228/15290 [00:05<06:28, 38.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 233/15290 [00:06<06:19, 39.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 237/15290 [00:06<06:18, 39.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 241/15290 [00:06<06:25, 39.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 245/15290 [00:06<06:37, 37.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 249/15290 [00:06<06:38, 37.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 253/15290 [00:06<06:40, 37.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 257/15290 [00:06<06:46, 36.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 261/15290 [00:06<06:40, 37.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 265/15290 [00:06<06:37, 37.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 269/15290 [00:07<06:48, 36.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 273/15290 [00:07<06:39, 37.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 278/15290 [00:07<06:32, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 282/15290 [00:07<08:33, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 286/15290 [00:07<08:00, 31.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 290/15290 [00:07<07:33, 33.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 294/15290 [00:07<07:14, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 298/15290 [00:07<06:58, 35.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 303/15290 [00:08<06:42, 37.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 308/15290 [00:08<06:27, 38.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 312/15290 [00:08<06:29, 38.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 316/15290 [00:08<06:33, 38.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 320/15290 [00:08<06:44, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 324/15290 [00:08<06:44, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 329/15290 [00:08<06:32, 38.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 333/15290 [00:08<06:32, 38.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 337/15290 [00:08<06:35, 37.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 341/15290 [00:09<06:35, 37.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 345/15290 [00:09<06:35, 37.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 349/15290 [00:09<06:40, 37.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 353/15290 [00:09<06:41, 37.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 357/15290 [00:09<06:40, 37.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 361/15290 [00:09<06:37, 37.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 365/15290 [00:09<06:56, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 369/15290 [00:09<06:56, 35.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 373/15290 [00:09<06:51, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 377/15290 [00:10<06:39, 37.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  2%|▏         | 381/15290 [00:10<06:32, 37.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 385/15290 [00:10<06:28, 38.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 390/15290 [00:10<06:19, 39.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 394/15290 [00:10<06:29, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 398/15290 [00:10<07:04, 35.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 402/15290 [00:10<07:16, 34.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 406/15290 [00:10<07:13, 34.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 410/15290 [00:10<07:14, 34.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 414/15290 [00:11<07:15, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 418/15290 [00:11<07:14, 34.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 422/15290 [00:11<07:15, 34.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 426/15290 [00:11<06:56, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 431/15290 [00:11<06:43, 36.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 435/15290 [00:11<06:35, 37.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 440/15290 [00:11<06:27, 38.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 445/15290 [00:11<06:18, 39.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 449/15290 [00:11<06:20, 39.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 454/15290 [00:12<06:12, 39.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 459/15290 [00:12<06:06, 40.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 464/15290 [00:12<06:18, 39.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 468/15290 [00:12<06:23, 38.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 472/15290 [00:12<06:20, 38.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 476/15290 [00:12<06:19, 39.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 480/15290 [00:12<06:17, 39.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 484/15290 [00:12<06:18, 39.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 488/15290 [00:12<06:18, 39.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 492/15290 [00:13<06:20, 38.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 496/15290 [00:13<06:32, 37.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 500/15290 [00:13<06:26, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 504/15290 [00:13<06:23, 38.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 508/15290 [00:13<06:23, 38.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 512/15290 [00:13<06:19, 38.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 516/15290 [00:13<06:31, 37.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 520/15290 [00:13<06:27, 38.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 524/15290 [00:13<07:08, 34.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 528/15290 [00:14<06:55, 35.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  3%|▎         | 533/15290 [00:14<06:34, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 538/15290 [00:14<06:22, 38.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 542/15290 [00:14<06:20, 38.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 546/15290 [00:14<06:19, 38.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 550/15290 [00:14<06:34, 37.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 554/15290 [00:14<07:04, 34.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 558/15290 [00:14<07:13, 33.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 562/15290 [00:14<06:54, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 566/15290 [00:15<06:54, 35.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▎         | 571/15290 [00:15<06:36, 37.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 576/15290 [00:15<06:22, 38.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 580/15290 [00:15<06:57, 35.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 584/15290 [00:15<06:57, 35.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 588/15290 [00:15<07:05, 34.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 592/15290 [00:15<07:06, 34.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 597/15290 [00:15<06:48, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 601/15290 [00:16<06:50, 35.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 605/15290 [00:16<06:47, 36.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 610/15290 [00:16<06:27, 37.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 615/15290 [00:16<06:14, 39.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 620/15290 [00:16<06:13, 39.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 624/15290 [00:16<06:16, 38.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 629/15290 [00:16<06:10, 39.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 633/15290 [00:16<06:11, 39.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 638/15290 [00:16<06:08, 39.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 642/15290 [00:17<06:11, 39.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 646/15290 [00:17<06:10, 39.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 650/15290 [00:17<06:13, 39.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 654/15290 [00:17<06:37, 36.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 658/15290 [00:17<06:35, 36.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 663/15290 [00:17<06:14, 39.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 668/15290 [00:17<06:03, 40.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 673/15290 [00:17<05:57, 40.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 678/15290 [00:18<05:58, 40.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 683/15290 [00:18<06:18, 38.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  4%|▍         | 687/15290 [00:18<07:03, 34.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 692/15290 [00:18<06:44, 36.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 696/15290 [00:18<06:52, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 700/15290 [00:18<06:50, 35.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 705/15290 [00:18<06:26, 37.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 710/15290 [00:18<06:16, 38.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 714/15290 [00:19<06:18, 38.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 719/15290 [00:19<06:10, 39.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 723/15290 [00:19<06:09, 39.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 728/15290 [00:19<06:04, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 732/15290 [00:19<06:04, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 736/15290 [00:19<06:05, 39.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 740/15290 [00:19<06:09, 39.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 744/15290 [00:19<06:09, 39.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 748/15290 [00:19<06:37, 36.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 752/15290 [00:19<06:39, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 756/15290 [00:20<06:36, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 760/15290 [00:20<06:29, 37.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▍         | 764/15290 [00:20<06:28, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 768/15290 [00:20<06:24, 37.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 773/15290 [00:20<06:16, 38.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 777/15290 [00:20<06:21, 38.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 781/15290 [00:20<06:19, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 785/15290 [00:20<06:49, 35.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 789/15290 [00:20<06:51, 35.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 793/15290 [00:21<06:49, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 797/15290 [00:21<06:57, 34.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 801/15290 [00:21<07:02, 34.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 805/15290 [00:21<07:05, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 809/15290 [00:21<07:00, 34.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 813/15290 [00:21<06:56, 34.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 817/15290 [00:21<07:09, 33.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 821/15290 [00:21<07:12, 33.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 825/15290 [00:22<06:58, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 830/15290 [00:22<06:42, 35.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 834/15290 [00:22<07:05, 33.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  5%|▌         | 838/15290 [00:22<06:58, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 843/15290 [00:22<06:33, 36.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 847/15290 [00:22<06:28, 37.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 851/15290 [00:22<06:27, 37.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 855/15290 [00:22<06:27, 37.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 859/15290 [00:22<06:29, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 863/15290 [00:23<06:31, 36.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 867/15290 [00:23<06:33, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 871/15290 [00:23<06:30, 36.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 875/15290 [00:23<06:35, 36.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 879/15290 [00:23<06:28, 37.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 883/15290 [00:23<06:35, 36.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 887/15290 [00:23<06:32, 36.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 891/15290 [00:23<06:35, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 895/15290 [00:23<06:36, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 899/15290 [00:24<06:26, 37.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 903/15290 [00:24<06:27, 37.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 907/15290 [00:24<06:33, 36.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 911/15290 [00:24<06:39, 35.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 915/15290 [00:24<06:43, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 919/15290 [00:24<06:46, 35.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 923/15290 [00:24<06:45, 35.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 927/15290 [00:24<06:43, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 931/15290 [00:24<06:49, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 935/15290 [00:25<06:38, 36.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 939/15290 [00:25<06:41, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 943/15290 [00:25<06:31, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 947/15290 [00:25<07:32, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 951/15290 [00:25<08:04, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▌         | 955/15290 [00:25<07:43, 30.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 959/15290 [00:25<07:22, 32.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 964/15290 [00:25<06:53, 34.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 968/15290 [00:26<06:44, 35.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 973/15290 [00:26<06:30, 36.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 977/15290 [00:26<06:22, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 981/15290 [00:26<06:20, 37.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 985/15290 [00:26<06:40, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  6%|▋         | 989/15290 [00:26<06:37, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 994/15290 [00:26<06:19, 37.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 999/15290 [00:26<06:09, 38.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1003/15290 [00:26<06:13, 38.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1008/15290 [00:27<06:10, 38.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1012/15290 [00:27<06:07, 38.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1016/15290 [00:27<06:07, 38.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1021/15290 [00:27<06:00, 39.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1026/15290 [00:27<05:56, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1030/15290 [00:27<05:59, 39.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1034/15290 [00:27<06:04, 39.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1038/15290 [00:27<06:17, 37.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1042/15290 [00:27<06:19, 37.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1046/15290 [00:28<06:14, 38.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1051/15290 [00:28<06:04, 39.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1055/15290 [00:28<06:33, 36.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1059/15290 [00:28<07:06, 33.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1063/15290 [00:28<07:10, 33.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1067/15290 [00:28<07:15, 32.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1071/15290 [00:28<06:59, 33.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1075/15290 [00:28<06:55, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1079/15290 [00:29<07:00, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1084/15290 [00:29<06:29, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1089/15290 [00:29<06:21, 37.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1093/15290 [00:29<06:23, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1097/15290 [00:29<06:17, 37.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1101/15290 [00:29<06:12, 38.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1105/15290 [00:29<06:15, 37.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1109/15290 [00:29<06:17, 37.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1113/15290 [00:29<06:13, 37.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1118/15290 [00:30<06:05, 38.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1123/15290 [00:30<05:58, 39.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1127/15290 [00:30<05:57, 39.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1132/15290 [00:30<05:49, 40.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1137/15290 [00:30<06:36, 35.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1141/15290 [00:30<06:30, 36.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  7%|▋         | 1146/15290 [00:30<06:18, 37.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1150/15290 [00:30<06:16, 37.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1154/15290 [00:31<06:12, 37.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1158/15290 [00:31<06:08, 38.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1162/15290 [00:31<06:04, 38.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1166/15290 [00:31<06:04, 38.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1171/15290 [00:31<05:57, 39.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1175/15290 [00:31<06:01, 39.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1179/15290 [00:31<06:02, 38.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1184/15290 [00:31<05:53, 39.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1188/15290 [00:31<06:03, 38.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1192/15290 [00:32<06:15, 37.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1196/15290 [00:32<06:23, 36.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1200/15290 [00:32<06:25, 36.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1204/15290 [00:32<06:28, 36.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1208/15290 [00:32<06:30, 36.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1212/15290 [00:32<06:34, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1216/15290 [00:32<06:41, 35.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1220/15290 [00:32<06:38, 35.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1225/15290 [00:32<06:18, 37.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1229/15290 [00:33<06:10, 37.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1233/15290 [00:33<06:09, 38.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1237/15290 [00:33<06:38, 35.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1241/15290 [00:33<06:37, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1245/15290 [00:33<06:44, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1250/15290 [00:33<06:19, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1255/15290 [00:33<06:05, 38.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1260/15290 [00:33<05:53, 39.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1264/15290 [00:33<06:01, 38.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1269/15290 [00:34<05:57, 39.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1274/15290 [00:34<05:52, 39.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1278/15290 [00:34<05:59, 39.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1282/15290 [00:34<06:12, 37.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1286/15290 [00:34<06:15, 37.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1291/15290 [00:34<06:01, 38.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1295/15290 [00:34<06:01, 38.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  8%|▊         | 1299/15290 [00:34<06:05, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1304/15290 [00:35<05:52, 39.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1308/15290 [00:35<05:51, 39.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1312/15290 [00:35<05:52, 39.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1317/15290 [00:35<05:48, 40.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1322/15290 [00:35<05:55, 39.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1326/15290 [00:35<05:57, 39.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1330/15290 [00:35<05:58, 38.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▊         | 1334/15290 [00:35<06:04, 38.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1338/15290 [00:35<06:10, 37.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1342/15290 [00:35<06:04, 38.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1346/15290 [00:36<06:01, 38.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1350/15290 [00:36<06:16, 37.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1354/15290 [00:36<06:13, 37.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1358/15290 [00:36<06:21, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1362/15290 [00:36<06:28, 35.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1366/15290 [00:36<06:22, 36.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1370/15290 [00:36<06:25, 36.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1374/15290 [00:36<06:34, 35.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1378/15290 [00:36<06:30, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1382/15290 [00:37<06:31, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1386/15290 [00:37<06:31, 35.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1390/15290 [00:37<06:31, 35.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1394/15290 [00:37<06:41, 34.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1398/15290 [00:37<06:37, 34.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1402/15290 [00:37<06:34, 35.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1406/15290 [00:37<06:43, 34.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1410/15290 [00:37<06:46, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1414/15290 [00:38<06:44, 34.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1418/15290 [00:38<06:44, 34.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1422/15290 [00:38<06:35, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1426/15290 [00:38<06:30, 35.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1430/15290 [00:38<06:52, 33.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1434/15290 [00:38<06:41, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1438/15290 [00:38<06:43, 34.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1442/15290 [00:38<06:36, 34.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1446/15290 [00:38<06:25, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
  9%|▉         | 1450/15290 [00:39<06:17, 36.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1454/15290 [00:39<06:18, 36.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1458/15290 [00:39<06:13, 37.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1462/15290 [00:39<06:12, 37.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1466/15290 [00:39<06:17, 36.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1470/15290 [00:39<06:13, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1474/15290 [00:39<06:25, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1478/15290 [00:39<06:15, 36.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1482/15290 [00:39<06:30, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1486/15290 [00:40<06:21, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1490/15290 [00:40<06:24, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1494/15290 [00:40<06:57, 33.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1498/15290 [00:40<06:50, 33.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1502/15290 [00:40<06:42, 34.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1506/15290 [00:40<06:36, 34.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1510/15290 [00:40<06:38, 34.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1514/15290 [00:40<06:31, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1518/15290 [00:40<06:22, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1522/15290 [00:41<06:27, 35.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|▉         | 1526/15290 [00:41<06:23, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1530/15290 [00:41<06:15, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1534/15290 [00:41<06:08, 37.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1538/15290 [00:41<06:20, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1542/15290 [00:41<06:23, 35.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1546/15290 [00:41<06:26, 35.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1550/15290 [00:41<06:22, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1554/15290 [00:41<06:18, 36.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1558/15290 [00:42<06:18, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1562/15290 [00:42<06:15, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1566/15290 [00:42<06:17, 36.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1570/15290 [00:42<06:16, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1574/15290 [00:42<06:10, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1578/15290 [00:42<06:15, 36.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1582/15290 [00:42<06:05, 37.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1586/15290 [00:42<06:07, 37.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1591/15290 [00:42<05:56, 38.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1595/15290 [00:43<08:11, 27.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1599/15290 [00:43<08:00, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 10%|█         | 1603/15290 [00:43<07:32, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1607/15290 [00:43<07:37, 29.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1611/15290 [00:43<07:08, 31.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1615/15290 [00:43<06:45, 33.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1619/15290 [00:43<06:27, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1623/15290 [00:43<06:21, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1627/15290 [00:44<06:19, 35.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1631/15290 [00:44<06:52, 33.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1635/15290 [00:44<06:50, 33.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1640/15290 [00:44<06:23, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1644/15290 [00:44<06:19, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1648/15290 [00:44<06:38, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1652/15290 [00:44<06:48, 33.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1656/15290 [00:44<06:36, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1660/15290 [00:45<06:39, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1664/15290 [00:45<06:22, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1668/15290 [00:45<06:29, 34.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1672/15290 [00:45<06:26, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1676/15290 [00:45<06:13, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1681/15290 [00:45<06:00, 37.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1686/15290 [00:45<05:50, 38.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1690/15290 [00:45<05:59, 37.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1694/15290 [00:45<06:04, 37.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1698/15290 [00:46<06:05, 37.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1702/15290 [00:46<05:59, 37.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1706/15290 [00:46<05:53, 38.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1711/15290 [00:46<05:45, 39.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1715/15290 [00:46<05:48, 38.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█         | 1719/15290 [00:46<05:49, 38.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1723/15290 [00:46<05:49, 38.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1727/15290 [00:46<05:56, 38.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1731/15290 [00:46<06:01, 37.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1735/15290 [00:47<05:54, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1739/15290 [00:47<05:53, 38.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1743/15290 [00:47<06:10, 36.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1747/15290 [00:47<06:36, 34.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1751/15290 [00:47<06:23, 35.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 11%|█▏        | 1755/15290 [00:47<06:13, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1759/15290 [00:47<06:05, 37.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1763/15290 [00:47<06:09, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1767/15290 [00:47<06:09, 36.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1771/15290 [00:48<06:00, 37.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1776/15290 [00:48<05:47, 38.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1780/15290 [00:48<06:05, 36.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1784/15290 [00:48<06:23, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1788/15290 [00:48<06:14, 36.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1792/15290 [00:48<06:05, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1796/15290 [00:48<06:07, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1800/15290 [00:48<06:03, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1804/15290 [00:48<06:00, 37.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1808/15290 [00:49<06:05, 36.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1812/15290 [00:49<06:02, 37.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1816/15290 [00:49<06:14, 35.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1820/15290 [00:49<06:12, 36.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1824/15290 [00:49<06:15, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1828/15290 [00:49<06:12, 36.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1833/15290 [00:49<05:59, 37.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1837/15290 [00:49<06:20, 35.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1841/15290 [00:49<06:26, 34.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1846/15290 [00:50<06:09, 36.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1850/15290 [00:50<06:04, 36.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1854/15290 [00:50<05:58, 37.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1858/15290 [00:50<05:53, 38.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1863/15290 [00:50<05:43, 39.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1867/15290 [00:50<05:47, 38.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1871/15290 [00:50<05:44, 38.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1875/15290 [00:50<05:52, 38.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1879/15290 [00:50<05:51, 38.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1883/15290 [00:51<05:51, 38.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1887/15290 [00:51<05:48, 38.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1891/15290 [00:51<05:57, 37.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1895/15290 [00:51<05:51, 38.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1900/15290 [00:51<05:45, 38.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1904/15290 [00:51<05:55, 37.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 12%|█▏        | 1908/15290 [00:51<06:00, 37.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1912/15290 [00:51<06:11, 36.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1916/15290 [00:51<06:12, 35.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1920/15290 [00:52<06:12, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1924/15290 [00:52<06:07, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1928/15290 [00:52<06:18, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1932/15290 [00:52<06:29, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1936/15290 [00:52<07:28, 29.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1940/15290 [00:52<07:25, 29.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1944/15290 [00:52<06:56, 32.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1948/15290 [00:52<06:33, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1952/15290 [00:53<06:22, 34.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1956/15290 [00:53<06:23, 34.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1960/15290 [00:53<06:17, 35.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1964/15290 [00:53<06:15, 35.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1968/15290 [00:53<06:11, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1972/15290 [00:53<06:20, 34.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1976/15290 [00:53<06:14, 35.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1980/15290 [00:53<06:11, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1984/15290 [00:53<06:21, 34.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1988/15290 [00:54<06:20, 34.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1992/15290 [00:54<06:23, 34.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 1996/15290 [00:54<06:12, 35.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2000/15290 [00:54<06:04, 36.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2004/15290 [00:54<05:59, 36.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2008/15290 [00:54<06:15, 35.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2012/15290 [00:54<07:28, 29.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2016/15290 [00:54<07:15, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2020/15290 [00:55<07:12, 30.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2024/15290 [00:55<07:08, 30.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2028/15290 [00:55<06:44, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2032/15290 [00:55<06:25, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2036/15290 [00:55<06:11, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2040/15290 [00:55<06:14, 35.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2044/15290 [00:55<06:04, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2048/15290 [00:55<06:02, 36.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2052/15290 [00:55<06:04, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2056/15290 [00:56<05:56, 37.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2060/15290 [00:56<05:57, 37.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 13%|█▎        | 2064/15290 [00:56<06:07, 36.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2068/15290 [00:56<06:03, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2072/15290 [00:56<05:57, 37.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2076/15290 [00:56<05:49, 37.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2080/15290 [00:56<07:09, 30.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2084/15290 [00:56<07:03, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2088/15290 [00:56<06:47, 32.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2092/15290 [00:57<06:35, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2096/15290 [00:57<06:21, 34.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▎        | 2100/15290 [00:57<06:13, 35.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2104/15290 [00:57<06:15, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2108/15290 [00:57<06:19, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2112/15290 [00:57<06:26, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2116/15290 [00:57<06:29, 33.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2120/15290 [00:57<06:28, 33.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2124/15290 [00:58<06:18, 34.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2128/15290 [00:58<06:15, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2132/15290 [00:58<06:04, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2136/15290 [00:58<06:05, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2140/15290 [00:58<05:59, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2144/15290 [00:58<05:55, 36.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2148/15290 [00:58<05:52, 37.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2152/15290 [00:58<06:00, 36.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2156/15290 [00:58<06:01, 36.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2160/15290 [00:58<06:08, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2164/15290 [00:59<06:04, 35.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2168/15290 [00:59<05:57, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2172/15290 [00:59<05:49, 37.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2176/15290 [00:59<05:50, 37.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2180/15290 [00:59<05:56, 36.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2185/15290 [00:59<05:42, 38.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2190/15290 [00:59<05:37, 38.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2194/15290 [00:59<05:34, 39.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2198/15290 [00:59<05:36, 38.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2202/15290 [01:00<05:38, 38.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2206/15290 [01:00<05:43, 38.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2210/15290 [01:00<05:40, 38.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 14%|█▍        | 2214/15290 [01:00<05:52, 37.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2218/15290 [01:00<05:58, 36.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2222/15290 [01:00<06:15, 34.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2226/15290 [01:00<06:17, 34.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2230/15290 [01:00<06:11, 35.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2234/15290 [01:00<06:03, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2238/15290 [01:01<06:08, 35.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2242/15290 [01:01<06:20, 34.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2246/15290 [01:01<06:18, 34.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2251/15290 [01:01<05:57, 36.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2256/15290 [01:01<05:38, 38.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2260/15290 [01:01<05:39, 38.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2264/15290 [01:01<05:49, 37.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2268/15290 [01:01<05:54, 36.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2272/15290 [01:02<05:57, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2276/15290 [01:02<05:52, 36.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2280/15290 [01:02<06:09, 35.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2284/15290 [01:02<06:08, 35.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2288/15290 [01:02<06:15, 34.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▍        | 2292/15290 [01:02<06:54, 31.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2296/15290 [01:02<06:33, 33.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2300/15290 [01:02<06:14, 34.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2305/15290 [01:02<05:55, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2309/15290 [01:03<05:48, 37.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2313/15290 [01:03<05:42, 37.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2317/15290 [01:03<05:37, 38.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2321/15290 [01:03<06:14, 34.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2325/15290 [01:03<06:06, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2329/15290 [01:03<05:55, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2334/15290 [01:03<05:42, 37.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2338/15290 [01:03<05:45, 37.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2342/15290 [01:03<05:43, 37.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2346/15290 [01:04<05:41, 37.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2350/15290 [01:04<05:41, 37.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2354/15290 [01:04<05:51, 36.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2358/15290 [01:04<05:51, 36.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2362/15290 [01:04<05:44, 37.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 15%|█▌        | 2366/15290 [01:04<05:45, 37.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2370/15290 [01:04<05:49, 36.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2374/15290 [01:04<05:55, 36.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2378/15290 [01:04<05:51, 36.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2382/15290 [01:05<05:49, 36.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2386/15290 [01:05<05:50, 36.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2390/15290 [01:05<05:42, 37.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2394/15290 [01:05<05:48, 37.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2399/15290 [01:05<05:37, 38.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2403/15290 [01:05<05:43, 37.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2407/15290 [01:05<05:48, 36.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2411/15290 [01:05<05:42, 37.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2415/15290 [01:05<05:38, 38.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2419/15290 [01:06<05:34, 38.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2423/15290 [01:06<05:49, 36.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2427/15290 [01:06<05:50, 36.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2431/15290 [01:06<05:46, 37.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2435/15290 [01:06<05:40, 37.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2440/15290 [01:06<05:30, 38.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2444/15290 [01:06<05:31, 38.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2448/15290 [01:06<05:41, 37.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2452/15290 [01:06<05:38, 37.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2457/15290 [01:07<05:29, 38.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2461/15290 [01:07<05:35, 38.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2465/15290 [01:07<05:58, 35.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2469/15290 [01:07<05:52, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2473/15290 [01:07<05:48, 36.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2477/15290 [01:07<05:48, 36.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▌        | 2481/15290 [01:07<05:50, 36.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2485/15290 [01:07<05:54, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2489/15290 [01:07<05:59, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2493/15290 [01:08<05:48, 36.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2497/15290 [01:08<05:50, 36.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2501/15290 [01:08<05:43, 37.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2505/15290 [01:08<05:42, 37.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2509/15290 [01:08<05:55, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2513/15290 [01:08<06:09, 34.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2517/15290 [01:08<06:06, 34.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 16%|█▋        | 2521/15290 [01:08<06:10, 34.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2525/15290 [01:08<06:13, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2529/15290 [01:09<06:07, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2533/15290 [01:09<06:15, 33.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2537/15290 [01:09<06:26, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2541/15290 [01:09<06:17, 33.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2545/15290 [01:09<06:21, 33.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2549/15290 [01:09<06:15, 33.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2553/15290 [01:09<05:59, 35.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2557/15290 [01:09<05:49, 36.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2561/15290 [01:09<05:43, 37.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2565/15290 [01:10<05:45, 36.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2569/15290 [01:10<05:41, 37.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2573/15290 [01:10<05:46, 36.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2577/15290 [01:10<05:49, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2581/15290 [01:10<05:59, 35.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2585/15290 [01:10<06:11, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2589/15290 [01:10<06:17, 33.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2593/15290 [01:10<06:18, 33.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2597/15290 [01:11<06:24, 33.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2601/15290 [01:11<06:15, 33.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2605/15290 [01:11<06:30, 32.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2609/15290 [01:11<06:37, 31.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2613/15290 [01:11<06:29, 32.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2617/15290 [01:11<06:26, 32.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2621/15290 [01:11<06:19, 33.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2625/15290 [01:11<06:17, 33.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2629/15290 [01:11<06:18, 33.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2633/15290 [01:12<06:08, 34.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2637/15290 [01:12<06:04, 34.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2641/15290 [01:12<05:54, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2645/15290 [01:12<05:51, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2649/15290 [01:12<05:49, 36.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2653/15290 [01:12<05:45, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2657/15290 [01:12<05:51, 35.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2661/15290 [01:12<05:49, 36.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2665/15290 [01:13<06:48, 30.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2669/15290 [01:13<06:39, 31.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 17%|█▋        | 2673/15290 [01:13<06:19, 33.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2677/15290 [01:13<06:15, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2681/15290 [01:13<06:06, 34.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2685/15290 [01:13<06:09, 34.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2689/15290 [01:13<06:10, 33.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2693/15290 [01:13<06:07, 34.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2697/15290 [01:13<05:53, 35.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2702/15290 [01:14<05:39, 37.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2706/15290 [01:14<05:33, 37.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2710/15290 [01:14<05:39, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2714/15290 [01:14<05:39, 37.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2718/15290 [01:14<05:45, 36.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2722/15290 [01:14<05:57, 35.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2726/15290 [01:14<06:03, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2730/15290 [01:14<06:08, 34.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2734/15290 [01:14<06:10, 33.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2738/15290 [01:15<06:05, 34.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2742/15290 [01:15<06:06, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2746/15290 [01:15<06:07, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2750/15290 [01:15<05:59, 34.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2754/15290 [01:15<05:55, 35.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2758/15290 [01:15<05:49, 35.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2762/15290 [01:15<06:05, 34.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2766/15290 [01:15<06:02, 34.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2770/15290 [01:16<05:54, 35.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2774/15290 [01:16<05:45, 36.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2778/15290 [01:16<05:45, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2782/15290 [01:16<05:39, 36.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2786/15290 [01:16<05:34, 37.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2790/15290 [01:16<05:29, 37.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2794/15290 [01:16<05:27, 38.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2798/15290 [01:16<05:39, 36.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2802/15290 [01:16<05:43, 36.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2806/15290 [01:16<05:40, 36.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2810/15290 [01:17<05:32, 37.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2814/15290 [01:17<05:35, 37.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2819/15290 [01:17<05:24, 38.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2823/15290 [01:17<05:22, 38.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 18%|█▊        | 2827/15290 [01:17<05:23, 38.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2831/15290 [01:17<05:23, 38.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2835/15290 [01:17<05:28, 37.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2839/15290 [01:17<05:45, 36.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2843/15290 [01:17<05:44, 36.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2847/15290 [01:18<05:48, 35.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2851/15290 [01:18<05:46, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2855/15290 [01:18<05:40, 36.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2859/15290 [01:18<05:42, 36.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▊        | 2863/15290 [01:18<05:39, 36.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2867/15290 [01:18<05:39, 36.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2871/15290 [01:18<05:36, 36.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2875/15290 [01:18<05:37, 36.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2879/15290 [01:18<05:35, 36.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2883/15290 [01:19<05:34, 37.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2887/15290 [01:19<05:33, 37.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2891/15290 [01:19<05:34, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2895/15290 [01:19<05:33, 37.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2899/15290 [01:19<05:41, 36.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2903/15290 [01:19<05:56, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2907/15290 [01:19<06:03, 34.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2911/15290 [01:19<06:11, 33.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2915/15290 [01:19<06:17, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2919/15290 [01:20<06:06, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2923/15290 [01:20<05:57, 34.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2927/15290 [01:20<05:59, 34.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2931/15290 [01:20<05:58, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2936/15290 [01:20<05:43, 35.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2940/15290 [01:20<05:53, 34.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2944/15290 [01:20<05:58, 34.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2948/15290 [01:20<06:32, 31.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2952/15290 [01:21<06:31, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2956/15290 [01:21<06:31, 31.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2960/15290 [01:21<06:15, 32.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2964/15290 [01:21<06:04, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2968/15290 [01:21<05:52, 34.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2972/15290 [01:21<05:55, 34.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2976/15290 [01:21<05:54, 34.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 19%|█▉        | 2980/15290 [01:21<06:00, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 2984/15290 [01:22<05:55, 34.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 2988/15290 [01:22<06:00, 34.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 2992/15290 [01:22<06:01, 34.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 2996/15290 [01:22<06:06, 33.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3000/15290 [01:22<06:09, 33.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3004/15290 [01:22<06:11, 33.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3008/15290 [01:22<06:10, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3012/15290 [01:22<06:08, 33.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3016/15290 [01:22<05:59, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3020/15290 [01:23<05:50, 34.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3024/15290 [01:23<05:43, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3028/15290 [01:23<05:39, 36.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3032/15290 [01:23<05:32, 36.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3036/15290 [01:23<05:32, 36.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3040/15290 [01:23<06:01, 33.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3044/15290 [01:23<05:58, 34.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3048/15290 [01:23<06:09, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3052/15290 [01:24<06:13, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|█▉        | 3056/15290 [01:24<06:01, 33.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3060/15290 [01:24<05:57, 34.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3064/15290 [01:24<06:04, 33.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3068/15290 [01:24<05:54, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3072/15290 [01:24<05:53, 34.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3076/15290 [01:24<05:58, 34.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3080/15290 [01:24<05:57, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3084/15290 [01:24<05:58, 34.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3088/15290 [01:25<05:49, 34.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3092/15290 [01:25<05:57, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3096/15290 [01:25<05:55, 34.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3100/15290 [01:25<06:01, 33.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3104/15290 [01:25<05:55, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3108/15290 [01:25<05:56, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3112/15290 [01:25<05:55, 34.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3116/15290 [01:25<05:52, 34.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3120/15290 [01:25<05:59, 33.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3124/15290 [01:26<06:06, 33.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3128/15290 [01:26<06:08, 33.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 20%|██        | 3132/15290 [01:26<06:13, 32.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3136/15290 [01:26<06:04, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3140/15290 [01:26<06:09, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3144/15290 [01:26<06:08, 32.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3148/15290 [01:26<06:25, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3152/15290 [01:27<06:29, 31.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3156/15290 [01:27<06:42, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3160/15290 [01:27<06:38, 30.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3164/15290 [01:27<06:37, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3168/15290 [01:27<06:36, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3172/15290 [01:27<06:36, 30.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3176/15290 [01:27<07:07, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3180/15290 [01:27<06:42, 30.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3184/15290 [01:28<06:29, 31.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3188/15290 [01:28<06:16, 32.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3192/15290 [01:28<06:12, 32.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3196/15290 [01:28<06:08, 32.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3200/15290 [01:28<06:05, 33.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3204/15290 [01:28<05:50, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3208/15290 [01:28<05:47, 34.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3212/15290 [01:28<06:14, 32.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3216/15290 [01:29<06:17, 32.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3220/15290 [01:29<06:07, 32.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3224/15290 [01:29<05:55, 33.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3228/15290 [01:29<06:40, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3232/15290 [01:29<06:37, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3236/15290 [01:29<06:24, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3240/15290 [01:29<06:18, 31.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3244/15290 [01:29<06:13, 32.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██        | 3248/15290 [01:30<06:08, 32.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3252/15290 [01:30<06:07, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3256/15290 [01:30<06:07, 32.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3260/15290 [01:30<06:02, 33.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3264/15290 [01:30<05:53, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3268/15290 [01:30<05:46, 34.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3272/15290 [01:30<05:44, 34.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3276/15290 [01:30<05:39, 35.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3280/15290 [01:30<05:31, 36.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 21%|██▏       | 3284/15290 [01:31<05:34, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3288/15290 [01:31<05:37, 35.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3292/15290 [01:31<05:36, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3296/15290 [01:31<05:37, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3300/15290 [01:31<05:42, 35.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3304/15290 [01:31<05:35, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3308/15290 [01:31<05:31, 36.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3312/15290 [01:31<05:34, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3316/15290 [01:31<05:31, 36.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3320/15290 [01:32<06:07, 32.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3324/15290 [01:32<05:54, 33.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3328/15290 [01:32<05:46, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3332/15290 [01:32<05:38, 35.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3336/15290 [01:32<05:38, 35.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3340/15290 [01:32<05:28, 36.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3344/15290 [01:32<05:19, 37.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3349/15290 [01:32<05:10, 38.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3353/15290 [01:32<05:13, 38.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3357/15290 [01:33<05:50, 34.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3361/15290 [01:33<05:42, 34.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3365/15290 [01:33<05:34, 35.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3369/15290 [01:33<05:25, 36.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3373/15290 [01:33<05:27, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3377/15290 [01:33<05:25, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3381/15290 [01:33<05:22, 36.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3385/15290 [01:33<05:22, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3389/15290 [01:33<05:18, 37.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3393/15290 [01:34<05:23, 36.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3397/15290 [01:34<05:21, 36.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3401/15290 [01:34<05:33, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3405/15290 [01:34<05:23, 36.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3409/15290 [01:34<05:22, 36.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3413/15290 [01:34<05:19, 37.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3417/15290 [01:34<05:15, 37.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3421/15290 [01:34<05:11, 38.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3425/15290 [01:34<05:08, 38.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3429/15290 [01:35<05:13, 37.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3433/15290 [01:35<05:15, 37.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 22%|██▏       | 3437/15290 [01:35<05:09, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3441/15290 [01:35<05:10, 38.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3445/15290 [01:35<05:06, 38.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3449/15290 [01:35<05:04, 38.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3453/15290 [01:35<05:14, 37.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3457/15290 [01:35<05:09, 38.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3461/15290 [01:35<05:08, 38.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3465/15290 [01:35<05:06, 38.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3469/15290 [01:36<05:12, 37.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3473/15290 [01:36<05:31, 35.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3477/15290 [01:36<05:40, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3481/15290 [01:36<05:35, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3485/15290 [01:36<05:25, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3489/15290 [01:36<05:19, 36.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3493/15290 [01:36<05:16, 37.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3497/15290 [01:36<05:12, 37.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3501/15290 [01:36<05:08, 38.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3505/15290 [01:37<05:08, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3509/15290 [01:37<05:14, 37.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3513/15290 [01:37<05:20, 36.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3517/15290 [01:37<05:26, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3521/15290 [01:37<05:24, 36.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3525/15290 [01:37<05:23, 36.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3529/15290 [01:37<05:27, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3533/15290 [01:37<05:37, 34.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3537/15290 [01:37<05:29, 35.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3541/15290 [01:38<05:27, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3545/15290 [01:38<05:38, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3549/15290 [01:38<05:36, 34.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3553/15290 [01:38<05:29, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3557/15290 [01:38<05:23, 36.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3561/15290 [01:38<05:20, 36.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3565/15290 [01:38<05:18, 36.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3569/15290 [01:38<05:21, 36.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3573/15290 [01:38<05:21, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3577/15290 [01:39<05:19, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3581/15290 [01:39<05:16, 36.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3585/15290 [01:39<05:14, 37.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3589/15290 [01:39<05:21, 36.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 23%|██▎       | 3593/15290 [01:39<05:25, 35.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3597/15290 [01:39<05:22, 36.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3601/15290 [01:39<05:23, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3605/15290 [01:39<05:40, 34.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3609/15290 [01:39<05:48, 33.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3613/15290 [01:40<05:41, 34.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3617/15290 [01:40<05:42, 34.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3621/15290 [01:40<05:42, 34.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3625/15290 [01:40<05:42, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▎       | 3629/15290 [01:40<05:51, 33.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3633/15290 [01:40<05:55, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3637/15290 [01:40<06:03, 32.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3641/15290 [01:40<06:12, 31.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3645/15290 [01:41<06:22, 30.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3649/15290 [01:41<06:31, 29.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3653/15290 [01:41<06:25, 30.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3657/15290 [01:41<06:12, 31.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3661/15290 [01:41<06:01, 32.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3665/15290 [01:41<05:53, 32.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3669/15290 [01:41<05:47, 33.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3673/15290 [01:41<05:34, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3677/15290 [01:42<05:28, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3681/15290 [01:42<05:28, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3685/15290 [01:42<05:33, 34.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3689/15290 [01:42<05:21, 36.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3693/15290 [01:42<05:20, 36.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3697/15290 [01:42<05:24, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3701/15290 [01:42<05:30, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3705/15290 [01:42<05:30, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3709/15290 [01:42<05:28, 35.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3713/15290 [01:43<05:35, 34.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3717/15290 [01:43<05:36, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3721/15290 [01:43<05:35, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3725/15290 [01:43<05:35, 34.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3729/15290 [01:43<06:17, 30.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3733/15290 [01:43<06:09, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3737/15290 [01:43<05:50, 32.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3741/15290 [01:43<05:41, 33.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 24%|██▍       | 3745/15290 [01:44<05:31, 34.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3749/15290 [01:44<05:23, 35.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3753/15290 [01:44<05:24, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3757/15290 [01:44<05:23, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3761/15290 [01:44<05:25, 35.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3765/15290 [01:44<05:20, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3769/15290 [01:44<05:20, 36.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3773/15290 [01:44<05:23, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3777/15290 [01:44<05:27, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3781/15290 [01:45<05:25, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3785/15290 [01:45<05:17, 36.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3789/15290 [01:45<05:19, 35.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3793/15290 [01:45<05:41, 33.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3797/15290 [01:45<06:05, 31.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3801/15290 [01:45<06:10, 30.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3805/15290 [01:45<06:07, 31.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3809/15290 [01:45<05:56, 32.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3813/15290 [01:46<05:43, 33.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3817/15290 [01:46<05:42, 33.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▍       | 3821/15290 [01:46<05:54, 32.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3825/15290 [01:46<05:51, 32.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3829/15290 [01:46<05:45, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3833/15290 [01:46<05:43, 33.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3837/15290 [01:46<05:38, 33.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3841/15290 [01:46<05:48, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3845/15290 [01:46<05:43, 33.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3849/15290 [01:47<05:36, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3853/15290 [01:47<05:43, 33.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3857/15290 [01:47<05:33, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3861/15290 [01:47<05:24, 35.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3865/15290 [01:47<05:51, 32.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3869/15290 [01:47<05:54, 32.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3873/15290 [01:47<05:52, 32.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3877/15290 [01:47<05:42, 33.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3881/15290 [01:48<05:31, 34.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3885/15290 [01:48<05:25, 34.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3889/15290 [01:48<05:22, 35.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3893/15290 [01:48<05:22, 35.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 25%|██▌       | 3897/15290 [01:48<05:16, 36.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3901/15290 [01:48<05:13, 36.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3905/15290 [01:48<05:19, 35.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3909/15290 [01:48<05:34, 34.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3913/15290 [01:48<05:38, 33.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3917/15290 [01:49<05:41, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3921/15290 [01:49<05:45, 32.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3925/15290 [01:49<06:00, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3929/15290 [01:49<05:50, 32.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3933/15290 [01:49<05:38, 33.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3937/15290 [01:49<05:28, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3941/15290 [01:49<05:24, 34.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3945/15290 [01:49<05:23, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3949/15290 [01:50<05:23, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3953/15290 [01:50<05:26, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3957/15290 [01:50<05:25, 34.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3961/15290 [01:50<05:36, 33.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3965/15290 [01:50<05:33, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3969/15290 [01:50<05:35, 33.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3973/15290 [01:50<05:24, 34.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3977/15290 [01:50<05:26, 34.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3981/15290 [01:50<05:25, 34.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3985/15290 [01:51<05:16, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3989/15290 [01:51<05:22, 35.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3993/15290 [01:51<05:27, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 3997/15290 [01:51<05:28, 34.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 4001/15290 [01:51<05:36, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 4005/15290 [01:51<05:37, 33.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 4009/15290 [01:51<05:38, 33.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▌       | 4013/15290 [01:51<05:35, 33.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4017/15290 [01:52<05:28, 34.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4021/15290 [01:52<05:25, 34.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4025/15290 [01:52<05:15, 35.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4029/15290 [01:52<05:18, 35.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4033/15290 [01:52<05:15, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4037/15290 [01:52<05:20, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4041/15290 [01:52<05:15, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4045/15290 [01:52<05:12, 35.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 26%|██▋       | 4049/15290 [01:52<05:09, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4053/15290 [01:53<05:08, 36.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4057/15290 [01:53<05:07, 36.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4061/15290 [01:53<05:10, 36.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4065/15290 [01:53<05:03, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4069/15290 [01:53<05:00, 37.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4073/15290 [01:53<05:00, 37.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4077/15290 [01:53<05:02, 37.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4081/15290 [01:53<04:58, 37.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4085/15290 [01:53<05:02, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4089/15290 [01:54<05:13, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4093/15290 [01:54<05:10, 36.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4097/15290 [01:54<05:15, 35.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4101/15290 [01:54<05:32, 33.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4105/15290 [01:54<05:30, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4109/15290 [01:54<05:29, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4113/15290 [01:54<05:35, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4117/15290 [01:54<05:34, 33.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4121/15290 [01:54<05:26, 34.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4125/15290 [01:55<05:22, 34.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4129/15290 [01:55<05:24, 34.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4133/15290 [01:55<05:26, 34.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4137/15290 [01:55<05:20, 34.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4141/15290 [01:55<05:29, 33.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4145/15290 [01:55<05:26, 34.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4149/15290 [01:55<05:26, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4153/15290 [01:55<05:57, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4157/15290 [01:56<05:47, 32.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4161/15290 [01:56<05:50, 31.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4165/15290 [01:56<05:45, 32.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4169/15290 [01:56<05:45, 32.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4173/15290 [01:56<05:46, 32.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4177/15290 [01:56<05:35, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4181/15290 [01:56<05:32, 33.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4185/15290 [01:56<05:25, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4189/15290 [01:57<05:36, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4193/15290 [01:57<05:39, 32.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4197/15290 [01:57<05:42, 32.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 27%|██▋       | 4201/15290 [01:57<05:35, 33.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4205/15290 [01:57<05:30, 33.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4209/15290 [01:57<05:24, 34.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4213/15290 [01:57<05:29, 33.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4217/15290 [01:57<05:35, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4221/15290 [01:57<05:39, 32.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4225/15290 [01:58<05:37, 32.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4229/15290 [01:58<05:30, 33.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4233/15290 [01:58<05:28, 33.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4237/15290 [01:58<05:30, 33.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4241/15290 [01:58<05:28, 33.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4245/15290 [01:58<05:20, 34.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4249/15290 [01:58<05:17, 34.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4253/15290 [01:58<05:24, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4257/15290 [01:59<05:23, 34.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4261/15290 [01:59<05:14, 35.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4265/15290 [01:59<05:21, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4269/15290 [01:59<05:34, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4273/15290 [01:59<05:28, 33.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4277/15290 [01:59<05:21, 34.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4281/15290 [01:59<05:23, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4285/15290 [01:59<05:33, 33.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4289/15290 [01:59<05:30, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4293/15290 [02:00<05:40, 32.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4297/15290 [02:00<05:32, 33.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4301/15290 [02:00<05:37, 32.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4305/15290 [02:00<05:39, 32.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4309/15290 [02:00<05:44, 31.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4313/15290 [02:00<05:45, 31.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4317/15290 [02:00<05:51, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4321/15290 [02:01<05:55, 30.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4325/15290 [02:01<05:56, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4329/15290 [02:01<05:55, 30.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4333/15290 [02:01<05:55, 30.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4337/15290 [02:01<05:50, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4341/15290 [02:01<06:00, 30.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4345/15290 [02:01<05:54, 30.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4349/15290 [02:01<05:51, 31.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4353/15290 [02:02<05:55, 30.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 28%|██▊       | 4357/15290 [02:02<05:44, 31.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4361/15290 [02:02<05:42, 31.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4365/15290 [02:02<05:43, 31.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4369/15290 [02:02<05:39, 32.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4373/15290 [02:02<05:29, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4377/15290 [02:02<05:28, 33.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4381/15290 [02:02<05:26, 33.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4385/15290 [02:03<05:23, 33.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4389/15290 [02:03<05:18, 34.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▊       | 4393/15290 [02:03<05:12, 34.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4397/15290 [02:03<05:05, 35.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4401/15290 [02:03<05:22, 33.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4405/15290 [02:03<05:24, 33.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4409/15290 [02:03<05:24, 33.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4413/15290 [02:03<05:28, 33.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4417/15290 [02:03<05:24, 33.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4421/15290 [02:04<05:17, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4425/15290 [02:04<05:21, 33.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4429/15290 [02:04<05:19, 33.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4433/15290 [02:04<05:32, 32.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4437/15290 [02:04<05:27, 33.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4441/15290 [02:04<05:20, 33.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4445/15290 [02:04<05:19, 33.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4449/15290 [02:04<05:25, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4453/15290 [02:05<05:28, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4457/15290 [02:05<05:30, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4461/15290 [02:05<05:26, 33.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4465/15290 [02:05<05:28, 32.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4469/15290 [02:05<05:32, 32.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4473/15290 [02:05<05:34, 32.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4477/15290 [02:05<05:27, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4481/15290 [02:05<05:27, 33.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4485/15290 [02:05<05:24, 33.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4489/15290 [02:06<05:22, 33.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4493/15290 [02:06<05:31, 32.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4497/15290 [02:06<05:34, 32.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4501/15290 [02:06<05:48, 30.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4505/15290 [02:06<05:37, 31.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 29%|██▉       | 4509/15290 [02:06<05:40, 31.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4513/15290 [02:06<05:34, 32.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4517/15290 [02:06<05:23, 33.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4521/15290 [02:07<05:13, 34.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4525/15290 [02:07<05:07, 35.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4529/15290 [02:07<05:12, 34.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4533/15290 [02:07<05:10, 34.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4537/15290 [02:07<05:06, 35.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4541/15290 [02:07<05:06, 35.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4545/15290 [02:07<05:37, 31.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4549/15290 [02:07<05:33, 32.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4553/15290 [02:08<05:19, 33.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4557/15290 [02:08<05:22, 33.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4561/15290 [02:08<05:15, 34.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4565/15290 [02:08<05:04, 35.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4569/15290 [02:08<04:59, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4573/15290 [02:08<04:58, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4577/15290 [02:08<04:54, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4581/15290 [02:08<04:53, 36.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|██▉       | 4585/15290 [02:08<05:08, 34.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4589/15290 [02:09<05:13, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4593/15290 [02:09<05:09, 34.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4597/15290 [02:09<05:05, 34.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4601/15290 [02:09<05:04, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4605/15290 [02:09<05:00, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4609/15290 [02:09<04:59, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4613/15290 [02:09<04:59, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4617/15290 [02:09<04:58, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4621/15290 [02:09<04:57, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4625/15290 [02:10<04:55, 36.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4629/15290 [02:10<05:03, 35.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4633/15290 [02:10<05:21, 33.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4637/15290 [02:10<05:43, 31.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4641/15290 [02:10<05:59, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4645/15290 [02:10<05:56, 29.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4649/15290 [02:10<05:51, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4653/15290 [02:10<05:40, 31.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4657/15290 [02:11<05:53, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 30%|███       | 4661/15290 [02:11<05:55, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4665/15290 [02:11<05:45, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4669/15290 [02:11<05:27, 32.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4673/15290 [02:11<05:35, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4677/15290 [02:11<05:23, 32.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4681/15290 [02:11<05:37, 31.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4685/15290 [02:12<05:36, 31.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4689/15290 [02:12<05:23, 32.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4693/15290 [02:12<05:25, 32.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4697/15290 [02:12<05:18, 33.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4701/15290 [02:12<05:22, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4705/15290 [02:12<05:28, 32.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4709/15290 [02:12<05:15, 33.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4713/15290 [02:12<05:29, 32.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4717/15290 [02:12<05:27, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4721/15290 [02:13<05:39, 31.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4725/15290 [02:13<05:33, 31.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4729/15290 [02:13<05:30, 31.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4733/15290 [02:13<05:27, 32.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4737/15290 [02:13<05:14, 33.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4741/15290 [02:13<05:24, 32.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4745/15290 [02:13<05:27, 32.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4749/15290 [02:13<05:35, 31.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4753/15290 [02:14<05:48, 30.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4757/15290 [02:14<05:38, 31.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4761/15290 [02:14<05:44, 30.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4765/15290 [02:14<05:39, 31.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4769/15290 [02:14<05:52, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4773/15290 [02:14<05:53, 29.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███       | 4776/15290 [02:14<05:56, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4780/15290 [02:15<05:42, 30.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4784/15290 [02:15<05:46, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4788/15290 [02:15<05:38, 31.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4792/15290 [02:15<05:30, 31.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4796/15290 [02:15<05:32, 31.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4800/15290 [02:15<05:15, 33.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4804/15290 [02:15<05:30, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4808/15290 [02:15<05:29, 31.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4812/15290 [02:16<05:32, 31.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 31%|███▏      | 4816/15290 [02:16<05:39, 30.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4820/15290 [02:16<05:26, 32.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4824/15290 [02:16<05:30, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4828/15290 [02:16<05:19, 32.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4832/15290 [02:16<05:16, 33.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4836/15290 [02:16<05:25, 32.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4840/15290 [02:16<05:14, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4844/15290 [02:16<05:06, 34.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4848/15290 [02:17<05:29, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4852/15290 [02:17<05:19, 32.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4856/15290 [02:17<05:26, 31.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4860/15290 [02:17<05:27, 31.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4864/15290 [02:17<05:31, 31.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4868/15290 [02:17<05:36, 30.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4872/15290 [02:17<05:17, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4876/15290 [02:17<05:08, 33.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4880/15290 [02:18<04:56, 35.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4884/15290 [02:18<04:52, 35.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4888/15290 [02:18<04:51, 35.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4892/15290 [02:18<04:58, 34.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4896/15290 [02:18<05:11, 33.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4900/15290 [02:18<05:15, 32.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4904/15290 [02:18<05:18, 32.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4908/15290 [02:18<05:26, 31.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4912/15290 [02:19<05:11, 33.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4916/15290 [02:19<05:08, 33.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4920/15290 [02:19<05:07, 33.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4924/15290 [02:19<05:42, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4928/15290 [02:19<05:41, 30.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4932/15290 [02:19<05:31, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4936/15290 [02:19<05:20, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4940/15290 [02:19<05:46, 29.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4944/15290 [02:20<05:36, 30.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4948/15290 [02:20<05:24, 31.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4952/15290 [02:20<05:10, 33.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4956/15290 [02:20<05:00, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4960/15290 [02:20<04:55, 34.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4964/15290 [02:20<04:52, 35.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 32%|███▏      | 4968/15290 [02:20<04:48, 35.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4972/15290 [02:20<04:45, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4976/15290 [02:20<04:46, 36.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4980/15290 [02:21<04:46, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4984/15290 [02:21<04:47, 35.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4988/15290 [02:21<04:44, 36.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4992/15290 [02:21<04:41, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 4996/15290 [02:21<04:37, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5000/15290 [02:21<04:37, 37.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5004/15290 [02:21<04:37, 37.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5008/15290 [02:21<04:36, 37.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5012/15290 [02:21<04:35, 37.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5016/15290 [02:22<04:36, 37.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5020/15290 [02:22<04:46, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5024/15290 [02:22<05:05, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5028/15290 [02:22<05:17, 32.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5032/15290 [02:22<05:40, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5036/15290 [02:22<05:21, 31.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5040/15290 [02:22<05:11, 32.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5044/15290 [02:22<05:02, 33.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5048/15290 [02:23<05:00, 34.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5052/15290 [02:23<04:57, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5056/15290 [02:23<04:52, 34.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5060/15290 [02:23<05:36, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5064/15290 [02:23<05:22, 31.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5068/15290 [02:23<05:06, 33.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5072/15290 [02:23<05:00, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5076/15290 [02:23<05:15, 32.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5080/15290 [02:24<05:20, 31.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5084/15290 [02:24<05:09, 32.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5088/15290 [02:24<05:10, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5092/15290 [02:24<05:30, 30.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5096/15290 [02:24<05:23, 31.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5100/15290 [02:24<05:23, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5104/15290 [02:24<05:29, 30.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5108/15290 [02:24<05:15, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5112/15290 [02:25<05:05, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5116/15290 [02:25<04:58, 34.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 33%|███▎      | 5120/15290 [02:25<04:58, 34.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5124/15290 [02:25<04:56, 34.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5128/15290 [02:25<04:59, 33.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5132/15290 [02:25<04:57, 34.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5136/15290 [02:25<04:54, 34.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5140/15290 [02:25<04:51, 34.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5144/15290 [02:25<04:44, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5148/15290 [02:26<04:38, 36.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5152/15290 [02:26<04:39, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5156/15290 [02:26<04:37, 36.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▎      | 5160/15290 [02:26<04:36, 36.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5164/15290 [02:26<04:42, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5168/15290 [02:26<04:44, 35.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5172/15290 [02:26<04:41, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5176/15290 [02:26<04:53, 34.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5180/15290 [02:26<04:48, 35.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5184/15290 [02:27<04:44, 35.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5188/15290 [02:27<04:38, 36.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5192/15290 [02:27<04:36, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5196/15290 [02:27<04:40, 35.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5200/15290 [02:27<04:49, 34.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5204/15290 [02:27<04:45, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5208/15290 [02:27<04:45, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5212/15290 [02:27<05:05, 32.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5216/15290 [02:28<05:11, 32.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5220/15290 [02:28<05:11, 32.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5224/15290 [02:28<05:01, 33.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5228/15290 [02:28<04:55, 34.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5232/15290 [02:28<04:51, 34.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5236/15290 [02:28<04:56, 33.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5240/15290 [02:28<04:57, 33.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5244/15290 [02:28<05:04, 32.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5248/15290 [02:28<05:02, 33.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5252/15290 [02:29<05:01, 33.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5256/15290 [02:29<05:03, 33.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5260/15290 [02:29<05:02, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5264/15290 [02:29<05:09, 32.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5268/15290 [02:29<05:06, 32.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 34%|███▍      | 5272/15290 [02:29<05:00, 33.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5276/15290 [02:29<05:28, 30.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5280/15290 [02:29<05:26, 30.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5284/15290 [02:30<05:13, 31.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5288/15290 [02:30<05:05, 32.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5292/15290 [02:30<05:06, 32.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5296/15290 [02:30<05:11, 32.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5300/15290 [02:30<05:15, 31.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5304/15290 [02:30<05:15, 31.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5308/15290 [02:30<05:09, 32.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5312/15290 [02:30<05:05, 32.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5316/15290 [02:31<05:05, 32.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5320/15290 [02:31<05:02, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5324/15290 [02:31<04:58, 33.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5328/15290 [02:31<04:51, 34.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5332/15290 [02:31<04:46, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5336/15290 [02:31<04:42, 35.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5340/15290 [02:31<04:43, 35.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5344/15290 [02:31<04:40, 35.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▍      | 5348/15290 [02:31<04:43, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5352/15290 [02:32<04:40, 35.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5356/15290 [02:32<04:44, 34.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5360/15290 [02:32<04:38, 35.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5364/15290 [02:32<04:46, 34.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5368/15290 [02:32<04:48, 34.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5372/15290 [02:32<04:44, 34.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5376/15290 [02:32<04:46, 34.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5380/15290 [02:32<04:45, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5384/15290 [02:33<04:42, 35.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5388/15290 [02:33<04:39, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5392/15290 [02:33<04:36, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5396/15290 [02:33<04:36, 35.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5400/15290 [02:33<04:41, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5404/15290 [02:33<04:41, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5408/15290 [02:33<04:38, 35.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5412/15290 [02:33<04:35, 35.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5416/15290 [02:33<04:29, 36.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5420/15290 [02:33<04:30, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 35%|███▌      | 5424/15290 [02:34<04:29, 36.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5428/15290 [02:34<04:28, 36.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5432/15290 [02:34<04:30, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5436/15290 [02:34<04:28, 36.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5440/15290 [02:34<04:35, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5444/15290 [02:34<04:42, 34.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5448/15290 [02:34<04:38, 35.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5452/15290 [02:34<04:36, 35.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5456/15290 [02:35<04:34, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5460/15290 [02:35<04:31, 36.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5464/15290 [02:35<04:29, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5468/15290 [02:35<04:28, 36.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5472/15290 [02:35<04:27, 36.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5476/15290 [02:35<04:30, 36.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5480/15290 [02:35<04:37, 35.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5484/15290 [02:35<04:33, 35.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5488/15290 [02:36<06:21, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5491/15290 [02:36<06:38, 24.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5494/15290 [02:36<07:02, 23.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5497/15290 [02:36<06:45, 24.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5501/15290 [02:36<06:03, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5505/15290 [02:36<05:30, 29.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5509/15290 [02:36<05:12, 31.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5513/15290 [02:36<05:01, 32.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5517/15290 [02:36<04:54, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5521/15290 [02:37<04:48, 33.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5525/15290 [02:37<04:45, 34.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5529/15290 [02:37<04:36, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5533/15290 [02:37<04:35, 35.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5537/15290 [02:37<04:30, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▌      | 5541/15290 [02:37<05:11, 31.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5545/15290 [02:37<05:22, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5549/15290 [02:37<05:10, 31.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5553/15290 [02:38<04:58, 32.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5557/15290 [02:38<04:47, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5561/15290 [02:38<05:00, 32.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5565/15290 [02:38<05:08, 31.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5569/15290 [02:38<04:58, 32.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5573/15290 [02:38<04:49, 33.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 36%|███▋      | 5577/15290 [02:38<04:42, 34.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5581/15290 [02:38<04:36, 35.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5585/15290 [02:39<04:32, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5589/15290 [02:39<04:30, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5593/15290 [02:39<04:30, 35.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5597/15290 [02:39<04:33, 35.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5601/15290 [02:39<04:31, 35.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5605/15290 [02:39<04:25, 36.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5609/15290 [02:39<04:22, 36.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5613/15290 [02:39<04:28, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5617/15290 [02:39<04:40, 34.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5621/15290 [02:40<04:40, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5625/15290 [02:40<04:45, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5629/15290 [02:40<05:17, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5633/15290 [02:40<05:05, 31.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5637/15290 [02:40<05:26, 29.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5641/15290 [02:40<05:38, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5644/15290 [02:40<05:48, 27.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5647/15290 [02:40<05:50, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5651/15290 [02:41<05:37, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5655/15290 [02:41<05:27, 29.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5659/15290 [02:41<05:16, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5663/15290 [02:41<05:14, 30.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5667/15290 [02:41<05:09, 31.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5671/15290 [02:41<05:00, 32.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5675/15290 [02:41<04:59, 32.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5679/15290 [02:41<04:54, 32.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5683/15290 [02:42<04:58, 32.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5687/15290 [02:42<04:52, 32.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5691/15290 [02:42<04:52, 32.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5695/15290 [02:42<04:54, 32.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5699/15290 [02:42<04:58, 32.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5703/15290 [02:42<05:02, 31.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5707/15290 [02:42<05:05, 31.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5711/15290 [02:42<05:09, 30.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5715/15290 [02:43<05:05, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5719/15290 [02:43<05:03, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5723/15290 [02:43<04:57, 32.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5727/15290 [02:43<04:56, 32.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 37%|███▋      | 5731/15290 [02:43<04:58, 32.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5735/15290 [02:43<04:58, 32.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5739/15290 [02:43<05:11, 30.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5743/15290 [02:43<05:08, 30.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5747/15290 [02:44<05:06, 31.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5751/15290 [02:44<05:23, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5754/15290 [02:44<05:22, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5758/15290 [02:44<05:15, 30.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5762/15290 [02:44<05:12, 30.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5766/15290 [02:44<05:08, 30.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5770/15290 [02:44<04:59, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5774/15290 [02:44<04:59, 31.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5778/15290 [02:45<04:52, 32.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5782/15290 [02:45<04:46, 33.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5786/15290 [02:45<04:43, 33.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5790/15290 [02:45<04:39, 33.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5794/15290 [02:45<04:50, 32.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5798/15290 [02:45<05:14, 30.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5802/15290 [02:45<05:18, 29.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5806/15290 [02:46<05:16, 29.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5810/15290 [02:46<05:25, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5814/15290 [02:46<05:19, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5817/15290 [02:46<05:18, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5821/15290 [02:46<05:20, 29.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5824/15290 [02:46<05:33, 28.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5827/15290 [02:46<05:33, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5830/15290 [02:46<05:32, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5833/15290 [02:46<05:30, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5836/15290 [02:47<05:33, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5839/15290 [02:47<05:29, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5842/15290 [02:47<05:28, 28.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5845/15290 [02:47<05:25, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5849/15290 [02:47<05:14, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5853/15290 [02:47<05:14, 30.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5856/15290 [02:47<05:36, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5859/15290 [02:47<05:34, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5863/15290 [02:47<05:24, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5867/15290 [02:48<05:19, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5870/15290 [02:48<05:18, 29.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5873/15290 [02:48<05:18, 29.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5877/15290 [02:48<05:16, 29.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5880/15290 [02:48<05:18, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 38%|███▊      | 5884/15290 [02:48<05:12, 30.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5887/15290 [02:48<05:13, 29.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5891/15290 [02:48<05:00, 31.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5895/15290 [02:49<04:57, 31.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5899/15290 [02:49<04:50, 32.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5903/15290 [02:49<04:52, 32.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5907/15290 [02:49<04:57, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5911/15290 [02:49<04:57, 31.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5915/15290 [02:49<04:54, 31.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5919/15290 [02:49<04:58, 31.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▊      | 5923/15290 [02:49<05:02, 31.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5927/15290 [02:50<05:02, 31.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5931/15290 [02:50<05:07, 30.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5935/15290 [02:50<04:59, 31.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5939/15290 [02:50<04:50, 32.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5943/15290 [02:50<04:47, 32.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5947/15290 [02:50<04:47, 32.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5951/15290 [02:50<04:47, 32.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5955/15290 [02:50<04:50, 32.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5959/15290 [02:51<04:49, 32.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5963/15290 [02:51<04:53, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5967/15290 [02:51<04:48, 32.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5971/15290 [02:51<04:49, 32.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5975/15290 [02:51<04:45, 32.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5979/15290 [02:51<04:45, 32.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5983/15290 [02:51<04:47, 32.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5987/15290 [02:51<04:49, 32.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5991/15290 [02:52<04:56, 31.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5995/15290 [02:52<04:55, 31.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 5999/15290 [02:52<04:59, 31.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6003/15290 [02:52<04:55, 31.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6007/15290 [02:52<04:54, 31.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6011/15290 [02:52<04:56, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6015/15290 [02:52<04:45, 32.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6019/15290 [02:52<04:39, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6023/15290 [02:53<04:37, 33.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6027/15290 [02:53<04:34, 33.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6031/15290 [02:53<04:36, 33.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6035/15290 [02:53<04:32, 33.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 39%|███▉      | 6039/15290 [02:53<04:35, 33.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6043/15290 [02:53<04:32, 33.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6047/15290 [02:53<04:27, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6051/15290 [02:53<04:26, 34.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6055/15290 [02:53<04:26, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6059/15290 [02:54<04:25, 34.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6063/15290 [02:54<04:22, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6067/15290 [02:54<04:21, 35.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6071/15290 [02:54<04:20, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6075/15290 [02:54<04:23, 34.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6079/15290 [02:54<04:21, 35.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6083/15290 [02:54<04:31, 33.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6087/15290 [02:54<04:29, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6091/15290 [02:54<04:31, 33.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6095/15290 [02:55<04:29, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6099/15290 [02:55<04:36, 33.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6103/15290 [02:55<04:40, 32.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6107/15290 [02:55<04:42, 32.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6111/15290 [02:55<04:49, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|███▉      | 6115/15290 [02:55<04:47, 31.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6119/15290 [02:55<04:55, 31.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6123/15290 [02:56<04:54, 31.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6127/15290 [02:56<04:57, 30.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6131/15290 [02:56<04:54, 31.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6135/15290 [02:56<04:50, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6139/15290 [02:56<04:55, 31.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6143/15290 [02:56<04:53, 31.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6147/15290 [02:56<05:02, 30.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6151/15290 [02:56<05:03, 30.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6155/15290 [02:57<04:57, 30.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6159/15290 [02:57<04:50, 31.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6163/15290 [02:57<04:52, 31.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6167/15290 [02:57<04:49, 31.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6171/15290 [02:57<04:42, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6175/15290 [02:57<04:44, 32.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6179/15290 [02:57<05:06, 29.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6183/15290 [02:57<05:15, 28.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6186/15290 [02:58<05:33, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 40%|████      | 6189/15290 [02:58<05:44, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6193/15290 [02:58<05:22, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6197/15290 [02:58<04:58, 30.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6201/15290 [02:58<05:07, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6204/15290 [02:58<05:17, 28.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6207/15290 [02:58<06:06, 24.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6211/15290 [02:59<05:40, 26.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6215/15290 [02:59<05:17, 28.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6219/15290 [02:59<05:05, 29.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6223/15290 [02:59<05:19, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6226/15290 [02:59<05:52, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6230/15290 [02:59<05:24, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6233/15290 [02:59<05:25, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6236/15290 [02:59<05:29, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6239/15290 [03:00<05:23, 27.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6242/15290 [03:00<05:32, 27.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6246/15290 [03:00<05:11, 29.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6250/15290 [03:00<04:59, 30.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6254/15290 [03:00<05:21, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6258/15290 [03:00<05:11, 28.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6261/15290 [03:00<05:11, 29.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6264/15290 [03:00<05:11, 28.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6267/15290 [03:00<05:11, 29.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6270/15290 [03:01<05:20, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6273/15290 [03:01<05:35, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6277/15290 [03:01<05:20, 28.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6280/15290 [03:01<05:27, 27.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6283/15290 [03:01<05:38, 26.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6286/15290 [03:01<05:53, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6289/15290 [03:01<05:41, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6292/15290 [03:01<05:44, 26.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6295/15290 [03:02<05:41, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6299/15290 [03:02<05:12, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6303/15290 [03:02<04:54, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████      | 6307/15290 [03:02<04:55, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6311/15290 [03:02<04:53, 30.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6315/15290 [03:02<04:57, 30.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6319/15290 [03:02<04:58, 30.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6323/15290 [03:02<05:05, 29.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6326/15290 [03:03<05:28, 27.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6330/15290 [03:03<05:17, 28.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6334/15290 [03:03<05:03, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6338/15290 [03:03<04:56, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 41%|████▏     | 6342/15290 [03:03<04:53, 30.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6346/15290 [03:03<04:59, 29.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6350/15290 [03:03<04:52, 30.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6354/15290 [03:03<04:49, 30.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6358/15290 [03:04<04:50, 30.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6362/15290 [03:04<04:45, 31.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6366/15290 [03:04<04:40, 31.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6370/15290 [03:04<04:44, 31.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6374/15290 [03:04<04:41, 31.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6378/15290 [03:04<04:44, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6382/15290 [03:04<05:01, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6386/15290 [03:05<04:53, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6390/15290 [03:05<04:51, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6394/15290 [03:05<04:55, 30.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6398/15290 [03:05<04:45, 31.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6402/15290 [03:05<04:45, 31.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6406/15290 [03:05<04:43, 31.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6410/15290 [03:05<04:45, 31.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6414/15290 [03:05<04:46, 30.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6418/15290 [03:06<04:50, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6422/15290 [03:06<04:57, 29.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6425/15290 [03:06<05:02, 29.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6429/15290 [03:06<04:49, 30.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6433/15290 [03:06<04:39, 31.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6437/15290 [03:06<04:31, 32.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6441/15290 [03:06<04:26, 33.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6445/15290 [03:06<04:28, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6449/15290 [03:06<04:21, 33.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6453/15290 [03:07<04:25, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6457/15290 [03:07<04:23, 33.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6461/15290 [03:07<04:31, 32.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6465/15290 [03:07<04:31, 32.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6469/15290 [03:07<04:36, 31.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6473/15290 [03:07<04:39, 31.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6477/15290 [03:07<04:53, 30.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6481/15290 [03:08<04:53, 30.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6485/15290 [03:08<04:50, 30.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6489/15290 [03:08<04:53, 30.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6493/15290 [03:08<04:55, 29.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 42%|████▏     | 6496/15290 [03:08<04:58, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6499/15290 [03:08<04:59, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6502/15290 [03:08<05:00, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6505/15290 [03:08<04:59, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6509/15290 [03:08<04:50, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6513/15290 [03:09<05:33, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6516/15290 [03:09<05:48, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6520/15290 [03:09<05:17, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6524/15290 [03:09<04:51, 30.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6528/15290 [03:09<04:36, 31.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6532/15290 [03:09<04:27, 32.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6536/15290 [03:09<04:26, 32.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6540/15290 [03:10<04:31, 32.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6544/15290 [03:10<04:46, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6548/15290 [03:10<05:07, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6551/15290 [03:10<05:18, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6555/15290 [03:10<05:02, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6559/15290 [03:10<05:00, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6562/15290 [03:10<05:00, 29.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6566/15290 [03:10<04:49, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6570/15290 [03:11<04:39, 31.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6574/15290 [03:11<04:33, 31.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6578/15290 [03:11<04:31, 32.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6582/15290 [03:11<04:24, 32.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6586/15290 [03:11<04:19, 33.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6590/15290 [03:11<04:20, 33.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6594/15290 [03:11<04:12, 34.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6598/15290 [03:11<04:09, 34.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6602/15290 [03:11<04:17, 33.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6606/15290 [03:12<04:22, 33.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6610/15290 [03:12<04:24, 32.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6614/15290 [03:12<05:02, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6617/15290 [03:12<05:10, 27.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6621/15290 [03:12<04:51, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6625/15290 [03:12<04:44, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6629/15290 [03:12<05:30, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6633/15290 [03:13<05:09, 27.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6637/15290 [03:13<04:50, 29.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6641/15290 [03:13<04:37, 31.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6645/15290 [03:13<04:33, 31.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 43%|████▎     | 6649/15290 [03:13<05:32, 25.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6652/15290 [03:13<05:23, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6655/15290 [03:13<05:31, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6658/15290 [03:13<05:24, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6662/15290 [03:14<04:57, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6665/15290 [03:14<04:55, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6668/15290 [03:14<05:18, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6671/15290 [03:14<05:14, 27.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6675/15290 [03:14<04:54, 29.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6679/15290 [03:14<04:52, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6682/15290 [03:14<05:19, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▎     | 6686/15290 [03:14<05:08, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6690/15290 [03:15<04:50, 29.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6694/15290 [03:15<04:36, 31.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6698/15290 [03:15<04:28, 32.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6702/15290 [03:15<04:20, 32.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6706/15290 [03:15<04:13, 33.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6710/15290 [03:15<04:17, 33.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6714/15290 [03:15<04:24, 32.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6718/15290 [03:15<04:37, 30.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6722/15290 [03:16<04:31, 31.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6726/15290 [03:16<04:28, 31.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6730/15290 [03:16<04:38, 30.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6734/15290 [03:16<04:42, 30.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6738/15290 [03:16<05:30, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6741/15290 [03:16<05:29, 25.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6745/15290 [03:16<05:21, 26.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6748/15290 [03:17<05:23, 26.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6751/15290 [03:17<05:14, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6754/15290 [03:17<05:08, 27.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6758/15290 [03:17<04:55, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6761/15290 [03:17<04:52, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6764/15290 [03:17<04:57, 28.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6767/15290 [03:17<05:31, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6770/15290 [03:17<05:23, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6774/15290 [03:17<04:55, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6777/15290 [03:18<04:54, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6781/15290 [03:18<04:42, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6785/15290 [03:18<05:10, 27.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6788/15290 [03:18<05:21, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6792/15290 [03:18<05:05, 27.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6796/15290 [03:18<04:50, 29.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6800/15290 [03:18<04:43, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 44%|████▍     | 6804/15290 [03:18<04:36, 30.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6808/15290 [03:19<04:33, 30.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6812/15290 [03:19<04:27, 31.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6816/15290 [03:19<04:26, 31.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6820/15290 [03:19<04:27, 31.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6824/15290 [03:19<04:23, 32.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6828/15290 [03:19<04:17, 32.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6832/15290 [03:19<04:21, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6836/15290 [03:19<04:44, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6840/15290 [03:20<04:58, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6843/15290 [03:20<05:19, 26.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6846/15290 [03:20<05:36, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6849/15290 [03:20<05:22, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6853/15290 [03:20<05:01, 28.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6856/15290 [03:20<05:12, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6859/15290 [03:20<06:13, 22.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6863/15290 [03:21<05:37, 25.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6867/15290 [03:21<05:16, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6870/15290 [03:21<05:12, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6873/15290 [03:21<05:13, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▍     | 6877/15290 [03:21<05:01, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6881/15290 [03:21<04:43, 29.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6884/15290 [03:21<05:01, 27.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6887/15290 [03:21<05:24, 25.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6890/15290 [03:22<05:12, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6893/15290 [03:22<05:31, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6896/15290 [03:22<05:34, 25.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6899/15290 [03:22<05:18, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6903/15290 [03:22<04:55, 28.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6907/15290 [03:22<04:44, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6911/15290 [03:22<04:29, 31.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6915/15290 [03:22<04:23, 31.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6919/15290 [03:23<04:40, 29.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6923/15290 [03:23<04:46, 29.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6927/15290 [03:23<04:48, 29.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6930/15290 [03:23<04:57, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6934/15290 [03:23<04:47, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6937/15290 [03:23<04:47, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6940/15290 [03:23<05:05, 27.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6943/15290 [03:23<04:59, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6947/15290 [03:24<04:53, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6950/15290 [03:24<05:01, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 45%|████▌     | 6953/15290 [03:24<04:55, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6957/15290 [03:24<04:38, 29.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6961/15290 [03:24<04:27, 31.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6965/15290 [03:24<04:22, 31.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6969/15290 [03:24<04:24, 31.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6973/15290 [03:24<05:05, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6976/15290 [03:25<05:00, 27.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6980/15290 [03:25<04:43, 29.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6984/15290 [03:25<04:39, 29.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6988/15290 [03:25<04:33, 30.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6992/15290 [03:25<05:47, 23.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6995/15290 [03:25<06:57, 19.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 6998/15290 [03:26<06:35, 20.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7001/15290 [03:26<06:10, 22.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7005/15290 [03:26<05:28, 25.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7009/15290 [03:26<05:07, 26.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7012/15290 [03:26<05:33, 24.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7015/15290 [03:26<05:29, 25.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7018/15290 [03:26<05:28, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7021/15290 [03:26<05:36, 24.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7024/15290 [03:26<05:19, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7027/15290 [03:27<05:15, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7031/15290 [03:27<04:57, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7034/15290 [03:27<05:00, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7037/15290 [03:27<04:54, 28.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7041/15290 [03:27<04:50, 28.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7044/15290 [03:27<04:51, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7048/15290 [03:27<04:33, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7052/15290 [03:27<04:38, 29.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7055/15290 [03:28<04:50, 28.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7058/15290 [03:28<04:50, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7062/15290 [03:28<04:34, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7066/15290 [03:28<04:46, 28.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▌     | 7069/15290 [03:28<04:54, 27.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7073/15290 [03:28<04:42, 29.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7077/15290 [03:28<04:27, 30.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7081/15290 [03:28<04:20, 31.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7085/15290 [03:29<04:25, 30.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7089/15290 [03:29<04:24, 30.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7093/15290 [03:29<04:22, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7097/15290 [03:29<04:39, 29.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7100/15290 [03:29<04:48, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7104/15290 [03:29<04:40, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 46%|████▋     | 7108/15290 [03:29<04:39, 29.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7112/15290 [03:29<04:35, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7115/15290 [03:30<04:50, 28.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7118/15290 [03:30<04:56, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7121/15290 [03:30<04:59, 27.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7125/15290 [03:30<04:45, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7128/15290 [03:30<04:53, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7131/15290 [03:30<04:52, 27.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7135/15290 [03:30<04:38, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7139/15290 [03:30<04:32, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7143/15290 [03:31<04:22, 31.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7147/15290 [03:31<04:26, 30.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7151/15290 [03:31<04:18, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7155/15290 [03:31<04:12, 32.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7159/15290 [03:31<04:07, 32.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7163/15290 [03:31<04:11, 32.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7167/15290 [03:31<04:13, 32.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7171/15290 [03:31<04:28, 30.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7175/15290 [03:32<04:30, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7179/15290 [03:32<04:37, 29.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7182/15290 [03:32<04:38, 29.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7186/15290 [03:32<04:30, 29.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7190/15290 [03:32<04:28, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7194/15290 [03:32<04:23, 30.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7198/15290 [03:32<04:27, 30.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7202/15290 [03:32<04:29, 30.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7206/15290 [03:33<04:32, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7209/15290 [03:33<04:55, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7212/15290 [03:33<04:55, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7215/15290 [03:33<05:07, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7218/15290 [03:33<05:13, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7221/15290 [03:33<05:08, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7224/15290 [03:33<05:10, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7227/15290 [03:33<05:08, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7231/15290 [03:34<04:44, 28.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7235/15290 [03:34<04:31, 29.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7238/15290 [03:34<04:44, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7241/15290 [03:34<04:57, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7244/15290 [03:34<05:05, 26.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7247/15290 [03:34<05:09, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7251/15290 [03:34<04:47, 27.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7255/15290 [03:34<04:32, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 47%|████▋     | 7259/15290 [03:35<04:19, 30.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7263/15290 [03:35<04:35, 29.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7266/15290 [03:35<04:51, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7269/15290 [03:35<04:53, 27.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7273/15290 [03:35<04:37, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7276/15290 [03:35<04:39, 28.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7279/15290 [03:35<04:36, 29.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7282/15290 [03:35<04:37, 28.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7286/15290 [03:35<04:30, 29.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7290/15290 [03:36<04:25, 30.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7294/15290 [03:36<04:20, 30.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7298/15290 [03:36<04:17, 31.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7302/15290 [03:36<04:07, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7306/15290 [03:36<04:41, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7309/15290 [03:36<04:54, 27.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7312/15290 [03:36<05:01, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7315/15290 [03:37<05:03, 26.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7318/15290 [03:37<04:55, 26.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7322/15290 [03:37<04:47, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7326/15290 [03:37<04:29, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7330/15290 [03:37<04:19, 30.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7334/15290 [03:37<04:29, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7337/15290 [03:37<04:39, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7340/15290 [03:37<04:39, 28.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7343/15290 [03:37<04:52, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7346/15290 [03:38<04:54, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7349/15290 [03:38<04:46, 27.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7352/15290 [03:38<04:54, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7355/15290 [03:38<04:50, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7358/15290 [03:38<04:54, 26.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7361/15290 [03:38<04:54, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7365/15290 [03:38<04:37, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7368/15290 [03:38<04:36, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7371/15290 [03:38<04:37, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7375/15290 [03:39<04:28, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7379/15290 [03:39<04:14, 31.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7383/15290 [03:39<04:04, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7387/15290 [03:39<03:56, 33.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7391/15290 [03:39<03:55, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7395/15290 [03:39<04:11, 31.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7399/15290 [03:39<04:09, 31.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7403/15290 [03:39<04:25, 29.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7407/15290 [03:40<04:20, 30.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7411/15290 [03:40<04:32, 28.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 48%|████▊     | 7415/15290 [03:40<04:28, 29.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7418/15290 [03:40<04:37, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7421/15290 [03:40<04:40, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7424/15290 [03:40<04:35, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7427/15290 [03:40<04:41, 27.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7431/15290 [03:40<04:30, 29.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7434/15290 [03:41<04:31, 28.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7437/15290 [03:41<04:42, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7441/15290 [03:41<04:29, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7444/15290 [03:41<04:39, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7447/15290 [03:41<04:34, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▊     | 7451/15290 [03:41<04:14, 30.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7455/15290 [03:41<04:12, 31.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7459/15290 [03:41<04:11, 31.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7463/15290 [03:42<04:02, 32.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7467/15290 [03:42<03:58, 32.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7471/15290 [03:42<04:26, 29.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7475/15290 [03:42<04:31, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7479/15290 [03:42<04:28, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7482/15290 [03:42<04:29, 28.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7486/15290 [03:42<04:24, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7490/15290 [03:42<04:17, 30.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7494/15290 [03:43<04:31, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7498/15290 [03:43<04:24, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7501/15290 [03:43<04:35, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7504/15290 [03:43<04:39, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7508/15290 [03:43<04:24, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7511/15290 [03:43<04:27, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7514/15290 [03:43<04:34, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7518/15290 [03:43<04:23, 29.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7521/15290 [03:44<04:29, 28.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7524/15290 [03:44<04:32, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7528/15290 [03:44<04:17, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7532/15290 [03:44<04:31, 28.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7536/15290 [03:44<04:24, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7540/15290 [03:44<04:21, 29.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7543/15290 [03:44<04:26, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7547/15290 [03:44<04:16, 30.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7551/15290 [03:45<04:07, 31.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7555/15290 [03:45<03:58, 32.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7559/15290 [03:45<04:04, 31.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7563/15290 [03:45<04:02, 31.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 49%|████▉     | 7567/15290 [03:45<03:59, 32.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7571/15290 [03:45<03:58, 32.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7575/15290 [03:45<04:17, 29.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7579/15290 [03:45<04:42, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7583/15290 [03:46<04:33, 28.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7586/15290 [03:46<04:37, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7589/15290 [03:46<04:32, 28.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7593/15290 [03:46<04:16, 30.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7597/15290 [03:46<04:21, 29.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7600/15290 [03:46<04:21, 29.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7603/15290 [03:46<04:23, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7607/15290 [03:46<04:12, 30.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7611/15290 [03:47<04:14, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7615/15290 [03:47<04:22, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7618/15290 [03:47<04:20, 29.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7622/15290 [03:47<04:11, 30.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7626/15290 [03:47<04:23, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7630/15290 [03:47<04:16, 29.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7634/15290 [03:47<04:35, 27.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7637/15290 [03:47<04:40, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7641/15290 [03:48<04:34, 27.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|████▉     | 7644/15290 [03:48<04:44, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7648/15290 [03:48<04:29, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7651/15290 [03:48<04:36, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7654/15290 [03:48<04:43, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7658/15290 [03:48<04:26, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7661/15290 [03:48<04:39, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7664/15290 [03:48<04:35, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7667/15290 [03:49<04:35, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7670/15290 [03:49<04:50, 26.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7673/15290 [03:49<04:50, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7677/15290 [03:49<04:39, 27.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7680/15290 [03:49<04:46, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7683/15290 [03:49<04:40, 27.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7687/15290 [03:49<04:23, 28.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7690/15290 [03:49<04:41, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7693/15290 [03:50<04:44, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7697/15290 [03:50<04:26, 28.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7700/15290 [03:50<04:38, 27.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7703/15290 [03:50<04:39, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7707/15290 [03:50<04:28, 28.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7710/15290 [03:50<04:40, 26.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7714/15290 [03:50<04:23, 28.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7717/15290 [03:50<04:28, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 50%|█████     | 7720/15290 [03:50<04:38, 27.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7723/15290 [03:51<04:45, 26.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7726/15290 [03:51<04:54, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7730/15290 [03:51<04:31, 27.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7734/15290 [03:51<04:26, 28.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7737/15290 [03:51<04:26, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7741/15290 [03:51<04:16, 29.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7744/15290 [03:51<04:29, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7747/15290 [03:51<04:26, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7750/15290 [03:52<04:25, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7753/15290 [03:52<04:35, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7756/15290 [03:52<04:29, 27.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7759/15290 [03:52<04:24, 28.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7762/15290 [03:52<04:40, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7765/15290 [03:52<04:36, 27.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7768/15290 [03:52<04:46, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7771/15290 [03:52<04:50, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7774/15290 [03:52<04:46, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7778/15290 [03:53<04:28, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7781/15290 [03:53<04:41, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7784/15290 [03:53<04:43, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7788/15290 [03:53<04:26, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7792/15290 [03:53<04:20, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7795/15290 [03:53<04:19, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7798/15290 [03:53<04:28, 27.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7801/15290 [03:53<04:31, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7805/15290 [03:54<04:13, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7809/15290 [03:54<04:08, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7813/15290 [03:54<04:13, 29.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7817/15290 [03:54<04:06, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7821/15290 [03:54<04:08, 30.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7825/15290 [03:54<04:30, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7828/15290 [03:54<04:27, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7831/15290 [03:54<04:33, 27.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████     | 7834/15290 [03:55<04:29, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7838/15290 [03:55<04:23, 28.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7841/15290 [03:55<04:32, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7844/15290 [03:55<04:30, 27.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7848/15290 [03:55<04:16, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7851/15290 [03:55<04:25, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7855/15290 [03:55<04:15, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7858/15290 [03:55<04:15, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7861/15290 [03:56<04:19, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7865/15290 [03:56<04:06, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7869/15290 [03:56<04:02, 30.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 51%|█████▏    | 7873/15290 [03:56<04:09, 29.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7877/15290 [03:56<03:58, 31.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7881/15290 [03:56<04:14, 29.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7884/15290 [03:56<04:15, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7888/15290 [03:56<04:06, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7892/15290 [03:57<03:56, 31.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7896/15290 [03:57<03:56, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7900/15290 [03:57<03:53, 31.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7904/15290 [03:57<04:20, 28.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7907/15290 [03:57<04:22, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7911/15290 [03:57<04:09, 29.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7915/15290 [03:57<04:14, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7918/15290 [03:57<04:21, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7922/15290 [03:58<04:11, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7926/15290 [03:58<04:05, 30.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7930/15290 [03:58<04:11, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7933/15290 [03:58<04:15, 28.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7937/15290 [03:58<04:06, 29.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7941/15290 [03:58<03:56, 31.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7945/15290 [03:58<04:06, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7949/15290 [03:58<04:12, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7952/15290 [03:59<04:10, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7955/15290 [03:59<04:15, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7958/15290 [03:59<04:16, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7962/15290 [03:59<04:02, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7966/15290 [03:59<04:14, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7969/15290 [03:59<04:27, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7973/15290 [03:59<04:12, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7976/15290 [03:59<04:10, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7979/15290 [04:00<04:18, 28.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7982/15290 [04:00<04:20, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7985/15290 [04:00<04:16, 28.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7988/15290 [04:00<04:14, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7991/15290 [04:00<04:13, 28.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7995/15290 [04:00<04:02, 30.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 7999/15290 [04:00<03:56, 30.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8003/15290 [04:00<04:12, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8007/15290 [04:00<04:03, 29.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8011/15290 [04:01<04:04, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8014/15290 [04:01<04:08, 29.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8018/15290 [04:01<03:54, 31.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8022/15290 [04:01<04:14, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 52%|█████▏    | 8026/15290 [04:01<04:07, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8030/15290 [04:01<04:02, 29.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8034/15290 [04:01<03:53, 31.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8038/15290 [04:01<03:54, 30.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8042/15290 [04:02<04:02, 29.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8046/15290 [04:02<03:59, 30.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8050/15290 [04:02<04:02, 29.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8054/15290 [04:02<03:54, 30.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8058/15290 [04:02<03:56, 30.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8062/15290 [04:02<03:55, 30.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8066/15290 [04:02<04:00, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8070/15290 [04:03<04:18, 27.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8073/15290 [04:03<04:14, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8076/15290 [04:03<04:23, 27.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8079/15290 [04:03<04:22, 27.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8082/15290 [04:03<04:25, 27.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8085/15290 [04:03<04:27, 26.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8089/15290 [04:03<04:11, 28.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8092/15290 [04:03<04:38, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8095/15290 [04:04<04:38, 25.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8098/15290 [04:04<04:46, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8101/15290 [04:04<04:47, 25.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8104/15290 [04:04<04:41, 25.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8107/15290 [04:04<04:43, 25.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8111/15290 [04:04<04:33, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8114/15290 [04:04<04:52, 24.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8117/15290 [04:04<04:39, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8120/15290 [04:05<04:41, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8123/15290 [04:05<04:46, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8126/15290 [04:05<05:35, 21.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8129/15290 [04:05<06:45, 17.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8131/15290 [04:05<07:32, 15.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8133/15290 [04:05<08:01, 14.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8136/15290 [04:06<07:30, 15.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8139/15290 [04:06<06:27, 18.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8143/15290 [04:06<05:15, 22.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8147/15290 [04:06<04:30, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8151/15290 [04:06<04:02, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8155/15290 [04:06<04:04, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8159/15290 [04:06<04:03, 29.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8163/15290 [04:06<03:56, 30.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8167/15290 [04:07<04:04, 29.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8171/15290 [04:07<03:54, 30.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8175/15290 [04:07<03:48, 31.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 53%|█████▎    | 8179/15290 [04:07<04:05, 28.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8182/15290 [04:07<04:03, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8186/15290 [04:07<03:46, 31.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8190/15290 [04:07<03:37, 32.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8194/15290 [04:07<03:32, 33.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8198/15290 [04:08<03:49, 30.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8202/15290 [04:08<03:59, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8206/15290 [04:08<04:01, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8209/15290 [04:08<04:18, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8212/15290 [04:08<04:21, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8215/15290 [04:08<04:27, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▎    | 8218/15290 [04:08<04:33, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8221/15290 [04:08<04:29, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8225/15290 [04:09<04:12, 27.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8228/15290 [04:09<04:19, 27.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8231/15290 [04:09<04:21, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8235/15290 [04:09<04:06, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8238/15290 [04:09<04:12, 27.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8241/15290 [04:09<04:15, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8244/15290 [04:09<04:12, 27.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8248/15290 [04:09<04:03, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8252/15290 [04:09<03:54, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8256/15290 [04:10<03:45, 31.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8260/15290 [04:10<03:51, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8264/15290 [04:10<03:49, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8268/15290 [04:10<03:59, 29.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8271/15290 [04:10<04:17, 27.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8274/15290 [04:10<04:21, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8277/15290 [04:10<04:46, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8280/15290 [04:11<04:53, 23.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8283/15290 [04:11<04:39, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8286/15290 [04:11<04:39, 25.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8290/15290 [04:11<04:19, 27.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8294/15290 [04:11<03:51, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8298/15290 [04:11<03:34, 32.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8302/15290 [04:11<03:28, 33.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8306/15290 [04:11<04:04, 28.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8310/15290 [04:12<03:55, 29.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8314/15290 [04:12<03:53, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8318/15290 [04:12<03:50, 30.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8322/15290 [04:12<03:51, 30.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8326/15290 [04:12<04:03, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8329/15290 [04:12<04:03, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 54%|█████▍    | 8333/15290 [04:12<03:51, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8337/15290 [04:12<03:45, 30.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8341/15290 [04:13<03:45, 30.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8345/15290 [04:13<04:12, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8348/15290 [04:13<04:12, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8352/15290 [04:13<04:00, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8356/15290 [04:13<03:48, 30.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8360/15290 [04:13<04:05, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8363/15290 [04:13<04:01, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8367/15290 [04:13<03:49, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8371/15290 [04:14<03:48, 30.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8375/15290 [04:14<04:08, 27.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8379/15290 [04:14<04:01, 28.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8383/15290 [04:14<03:49, 30.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8387/15290 [04:14<03:50, 29.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8391/15290 [04:14<04:03, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8394/15290 [04:14<04:13, 27.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8397/15290 [04:15<04:07, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8401/15290 [04:15<03:55, 29.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8404/15290 [04:15<04:04, 28.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▍    | 8407/15290 [04:15<04:05, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8410/15290 [04:15<04:01, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8414/15290 [04:15<03:50, 29.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8418/15290 [04:15<03:52, 29.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8421/15290 [04:15<04:15, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8425/15290 [04:15<04:01, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8429/15290 [04:16<03:51, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8432/15290 [04:16<04:01, 28.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8435/15290 [04:16<04:05, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8439/15290 [04:16<03:50, 29.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8443/15290 [04:16<03:39, 31.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8447/15290 [04:16<03:34, 31.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8451/15290 [04:16<03:31, 32.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8455/15290 [04:16<03:25, 33.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8459/15290 [04:17<03:37, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8463/15290 [04:17<04:08, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8466/15290 [04:17<04:04, 27.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8470/15290 [04:17<03:53, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8473/15290 [04:17<03:56, 28.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8477/15290 [04:17<03:53, 29.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8481/15290 [04:17<03:43, 30.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 55%|█████▌    | 8485/15290 [04:17<03:38, 31.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8489/15290 [04:18<03:36, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8493/15290 [04:18<03:32, 31.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8497/15290 [04:18<03:34, 31.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8501/15290 [04:18<03:36, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8505/15290 [04:18<03:36, 31.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8509/15290 [04:18<03:49, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8512/15290 [04:18<03:52, 29.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8516/15290 [04:18<03:47, 29.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8520/15290 [04:19<03:42, 30.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8524/15290 [04:19<03:45, 30.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8528/15290 [04:19<03:43, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8532/15290 [04:19<03:45, 29.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8536/15290 [04:19<03:44, 30.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8540/15290 [04:19<03:46, 29.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8543/15290 [04:19<03:56, 28.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8546/15290 [04:20<03:53, 28.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8550/15290 [04:20<03:45, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8554/15290 [04:20<03:42, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8558/15290 [04:20<03:40, 30.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8562/15290 [04:20<03:34, 31.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8566/15290 [04:20<03:31, 31.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8570/15290 [04:20<03:32, 31.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8574/15290 [04:20<03:36, 30.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8578/15290 [04:21<03:41, 30.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8582/15290 [04:21<03:50, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8585/15290 [04:21<03:57, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8588/15290 [04:21<03:59, 28.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8591/15290 [04:21<03:56, 28.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8595/15290 [04:21<03:52, 28.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▌    | 8598/15290 [04:21<03:57, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8601/15290 [04:21<03:59, 27.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8604/15290 [04:21<04:00, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8607/15290 [04:22<04:21, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8610/15290 [04:22<04:13, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8613/15290 [04:22<04:07, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8616/15290 [04:22<04:19, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8619/15290 [04:22<04:22, 25.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8622/15290 [04:22<04:38, 23.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8625/15290 [04:22<04:31, 24.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8628/15290 [04:22<04:41, 23.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8631/15290 [04:23<04:48, 23.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8634/15290 [04:23<04:34, 24.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 56%|█████▋    | 8637/15290 [04:23<04:23, 25.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8640/15290 [04:23<04:16, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8644/15290 [04:23<03:59, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8647/15290 [04:23<03:58, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8651/15290 [04:23<03:48, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8654/15290 [04:23<03:47, 29.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8658/15290 [04:24<03:41, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8662/15290 [04:24<03:42, 29.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8666/15290 [04:24<03:39, 30.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8670/15290 [04:24<03:38, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8674/15290 [04:24<03:37, 30.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8678/15290 [04:24<03:40, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8681/15290 [04:24<03:48, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8684/15290 [04:24<03:47, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8687/15290 [04:25<03:46, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8690/15290 [04:25<03:47, 28.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8693/15290 [04:25<03:45, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8696/15290 [04:25<03:47, 28.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8699/15290 [04:25<03:48, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8703/15290 [04:25<03:44, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8706/15290 [04:25<03:44, 29.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8709/15290 [04:25<03:46, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8712/15290 [04:25<03:55, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8715/15290 [04:26<04:17, 25.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8718/15290 [04:26<04:33, 24.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8721/15290 [04:26<04:23, 24.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8724/15290 [04:26<04:19, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8727/15290 [04:26<04:13, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8730/15290 [04:26<04:03, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8734/15290 [04:26<03:45, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8738/15290 [04:26<03:43, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8741/15290 [04:26<03:56, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8744/15290 [04:27<03:57, 27.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8748/15290 [04:27<03:45, 28.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8752/15290 [04:27<03:47, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8755/15290 [04:27<03:54, 27.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8759/15290 [04:27<03:44, 29.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8763/15290 [04:27<03:39, 29.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8766/15290 [04:27<03:44, 29.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8769/15290 [04:27<03:51, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8772/15290 [04:28<03:57, 27.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8776/15290 [04:28<03:50, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8780/15290 [04:28<03:42, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8784/15290 [04:28<03:32, 30.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8788/15290 [04:28<03:38, 29.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 57%|█████▋    | 8791/15290 [04:28<03:43, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8794/15290 [04:28<03:43, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8797/15290 [04:28<03:50, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8800/15290 [04:29<03:50, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8804/15290 [04:29<03:44, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8807/15290 [04:29<03:49, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8811/15290 [04:29<03:36, 29.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8814/15290 [04:29<03:44, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8817/15290 [04:29<03:42, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8821/15290 [04:29<03:33, 30.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8825/15290 [04:29<03:26, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8829/15290 [04:29<03:28, 31.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8833/15290 [04:30<03:28, 30.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8837/15290 [04:30<03:31, 30.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8841/15290 [04:30<03:37, 29.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8844/15290 [04:30<03:38, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8847/15290 [04:30<03:38, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8850/15290 [04:30<03:39, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8854/15290 [04:30<03:41, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8857/15290 [04:30<03:45, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8860/15290 [04:31<03:43, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8863/15290 [04:31<03:45, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8866/15290 [04:31<03:54, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8869/15290 [04:31<03:53, 27.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8872/15290 [04:31<03:52, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8875/15290 [04:31<03:48, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8878/15290 [04:31<03:46, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8882/15290 [04:31<03:40, 29.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8886/15290 [04:31<03:33, 29.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8889/15290 [04:32<03:37, 29.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8892/15290 [04:32<03:38, 29.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8895/15290 [04:32<03:37, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8898/15290 [04:32<03:36, 29.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8901/15290 [04:32<03:40, 28.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8904/15290 [04:32<03:40, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8907/15290 [04:32<03:41, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8910/15290 [04:32<03:39, 29.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8913/15290 [04:32<03:49, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8916/15290 [04:33<03:52, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8919/15290 [04:33<04:01, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8922/15290 [04:33<03:54, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8926/15290 [04:33<03:43, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8929/15290 [04:33<03:43, 28.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8932/15290 [04:33<03:58, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8935/15290 [04:33<04:47, 22.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8938/15290 [04:33<04:51, 21.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8941/15290 [04:34<04:33, 23.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 58%|█████▊    | 8944/15290 [04:34<04:29, 23.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8947/15290 [04:34<04:38, 22.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8950/15290 [04:34<04:56, 21.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8953/15290 [04:34<04:44, 22.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8956/15290 [04:34<04:33, 23.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8959/15290 [04:34<04:24, 23.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8962/15290 [04:34<04:11, 25.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8965/15290 [04:35<04:11, 25.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8968/15290 [04:35<04:02, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8972/15290 [04:35<03:45, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8976/15290 [04:35<03:39, 28.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▊    | 8979/15290 [04:35<03:41, 28.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 8983/15290 [04:35<03:32, 29.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 8986/15290 [04:35<04:03, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 8989/15290 [04:35<04:35, 22.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 8992/15290 [04:36<04:39, 22.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 8995/15290 [04:36<05:01, 20.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 8998/15290 [04:36<05:11, 20.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9001/15290 [04:36<05:01, 20.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9004/15290 [04:36<05:02, 20.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9007/15290 [04:36<04:35, 22.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9011/15290 [04:36<04:04, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9015/15290 [04:37<03:46, 27.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9018/15290 [04:37<03:47, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9021/15290 [04:37<04:00, 26.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9026/15290 [04:37<03:28, 30.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9030/15290 [04:37<03:26, 30.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9035/15290 [04:37<03:04, 33.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9041/15290 [04:37<02:37, 39.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9046/15290 [04:37<02:34, 40.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9051/15290 [04:38<02:25, 42.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9056/15290 [04:38<02:25, 42.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9062/15290 [04:38<02:17, 45.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9067/15290 [04:38<02:16, 45.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9072/15290 [04:38<02:13, 46.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9078/15290 [04:38<02:07, 48.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9084/15290 [04:38<02:02, 50.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9090/15290 [04:38<01:58, 52.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 59%|█████▉    | 9096/15290 [04:38<02:08, 48.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9101/15290 [04:39<02:19, 44.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9106/15290 [04:39<02:26, 42.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9111/15290 [04:39<02:29, 41.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9116/15290 [04:39<02:46, 37.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9120/15290 [04:39<02:52, 35.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9124/15290 [04:39<02:57, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9128/15290 [04:39<03:15, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9132/15290 [04:40<03:18, 30.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9136/15290 [04:40<03:23, 30.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9140/15290 [04:40<03:26, 29.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9144/15290 [04:40<03:25, 29.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9148/15290 [04:40<03:24, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9152/15290 [04:40<03:32, 28.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9155/15290 [04:40<03:33, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9158/15290 [04:40<03:42, 27.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9161/15290 [04:41<03:42, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9164/15290 [04:41<03:42, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9168/15290 [04:41<03:31, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|█████▉    | 9172/15290 [04:41<03:23, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9176/15290 [04:41<03:18, 30.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9180/15290 [04:41<03:21, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9184/15290 [04:41<03:23, 30.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9188/15290 [04:41<03:27, 29.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9191/15290 [04:42<03:27, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9195/15290 [04:42<03:21, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9199/15290 [04:42<03:24, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9202/15290 [04:42<03:31, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9205/15290 [04:42<03:32, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9209/15290 [04:42<03:25, 29.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9213/15290 [04:42<03:21, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9217/15290 [04:42<03:27, 29.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9220/15290 [04:43<03:31, 28.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9223/15290 [04:43<03:34, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9226/15290 [04:43<03:33, 28.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9229/15290 [04:43<03:47, 26.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9233/15290 [04:43<03:31, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9237/15290 [04:43<03:22, 29.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9240/15290 [04:43<03:37, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9243/15290 [04:43<03:41, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9246/15290 [04:43<03:40, 27.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 60%|██████    | 9249/15290 [04:44<03:38, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9252/15290 [04:44<03:38, 27.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9255/15290 [04:44<03:45, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9258/15290 [04:44<03:54, 25.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9262/15290 [04:44<03:33, 28.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9266/15290 [04:44<03:29, 28.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9269/15290 [04:44<04:02, 24.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9272/15290 [04:45<04:13, 23.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9276/15290 [04:45<03:49, 26.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9280/15290 [04:45<03:37, 27.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9283/15290 [04:45<03:41, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9286/15290 [04:45<03:40, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9290/15290 [04:45<03:25, 29.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9294/15290 [04:45<03:20, 29.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9297/15290 [04:45<03:55, 25.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9300/15290 [04:46<03:47, 26.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9303/15290 [04:46<03:48, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9306/15290 [04:46<03:50, 25.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9310/15290 [04:46<03:35, 27.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9314/15290 [04:46<03:26, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9317/15290 [04:46<03:26, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9320/15290 [04:46<03:47, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9323/15290 [04:46<03:57, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9326/15290 [04:46<03:56, 25.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9329/15290 [04:47<04:07, 24.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9332/15290 [04:47<04:01, 24.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9335/15290 [04:47<03:56, 25.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9338/15290 [04:47<03:48, 26.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9342/15290 [04:47<03:27, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9346/15290 [04:47<03:19, 29.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9349/15290 [04:47<03:39, 27.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9352/15290 [04:47<03:43, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9356/15290 [04:48<03:31, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9360/15290 [04:48<03:29, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████    | 9363/15290 [04:48<03:39, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9366/15290 [04:48<03:36, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9369/15290 [04:48<03:33, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9372/15290 [04:48<03:38, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9375/15290 [04:48<03:35, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9379/15290 [04:48<03:21, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9382/15290 [04:49<03:31, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9385/15290 [04:49<03:39, 26.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9389/15290 [04:49<03:25, 28.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9392/15290 [04:49<03:33, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9395/15290 [04:49<03:32, 27.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9399/15290 [04:49<03:22, 29.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 61%|██████▏   | 9402/15290 [04:49<03:24, 28.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9405/15290 [04:49<03:32, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9408/15290 [04:49<03:34, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9412/15290 [04:50<03:24, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9415/15290 [04:50<03:32, 27.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9418/15290 [04:50<03:29, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9422/15290 [04:50<03:14, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9426/15290 [04:50<03:31, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9429/15290 [04:50<03:35, 27.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9432/15290 [04:50<03:43, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9435/15290 [04:50<03:52, 25.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9438/15290 [04:51<03:43, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9441/15290 [04:51<03:53, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9444/15290 [04:51<03:51, 25.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9447/15290 [04:51<03:46, 25.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9450/15290 [04:51<03:41, 26.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9454/15290 [04:51<03:31, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9457/15290 [04:51<03:39, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9460/15290 [04:51<03:45, 25.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9463/15290 [04:52<03:42, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9466/15290 [04:52<03:43, 26.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9469/15290 [04:52<03:47, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9472/15290 [04:52<03:49, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9476/15290 [04:52<03:33, 27.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9479/15290 [04:52<03:41, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9482/15290 [04:52<03:41, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9485/15290 [04:52<03:50, 25.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9488/15290 [04:53<03:47, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9491/15290 [04:53<03:39, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9494/15290 [04:53<03:37, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9497/15290 [04:53<03:40, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9500/15290 [04:53<03:35, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9503/15290 [04:53<03:45, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9506/15290 [04:53<03:50, 25.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9509/15290 [04:53<03:45, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9512/15290 [04:53<03:37, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9515/15290 [04:54<03:38, 26.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9518/15290 [04:54<03:33, 27.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9521/15290 [04:54<03:28, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9524/15290 [04:54<03:38, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9527/15290 [04:54<03:42, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9530/15290 [04:54<03:37, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9533/15290 [04:54<03:34, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9537/15290 [04:54<03:23, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9540/15290 [04:54<03:24, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9543/15290 [04:55<03:27, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9547/15290 [04:55<03:19, 28.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9550/15290 [04:55<03:22, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9553/15290 [04:55<03:26, 27.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 62%|██████▏   | 9556/15290 [04:55<03:32, 26.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9559/15290 [04:55<03:28, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9563/15290 [04:55<03:21, 28.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9567/15290 [04:55<03:14, 29.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9570/15290 [04:55<03:16, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9573/15290 [04:56<03:15, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9576/15290 [04:56<03:16, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9580/15290 [04:56<03:09, 30.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9584/15290 [04:56<03:11, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9587/15290 [04:56<03:14, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9591/15290 [04:56<03:10, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9594/15290 [04:56<03:13, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9597/15290 [04:56<03:20, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9600/15290 [04:57<03:21, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9603/15290 [04:57<03:19, 28.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9606/15290 [04:57<03:17, 28.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9609/15290 [04:57<03:20, 28.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9612/15290 [04:57<03:23, 27.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9615/15290 [04:57<03:21, 28.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9618/15290 [04:57<03:32, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9621/15290 [04:57<03:30, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9624/15290 [04:57<03:29, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9627/15290 [04:58<03:35, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9630/15290 [04:58<03:44, 25.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9633/15290 [04:58<03:40, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9636/15290 [04:58<03:38, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9640/15290 [04:58<03:25, 27.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9644/15290 [04:58<03:12, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9648/15290 [04:58<03:04, 30.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9652/15290 [04:58<03:00, 31.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9656/15290 [04:58<03:00, 31.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9660/15290 [04:59<03:03, 30.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9664/15290 [04:59<03:08, 29.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9667/15290 [04:59<03:11, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9670/15290 [04:59<03:11, 29.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9673/15290 [04:59<03:18, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9676/15290 [04:59<03:21, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9679/15290 [04:59<03:23, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9682/15290 [04:59<03:18, 28.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9685/15290 [05:00<03:19, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9688/15290 [05:00<03:19, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9691/15290 [05:00<03:16, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9694/15290 [05:00<03:18, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9697/15290 [05:00<03:23, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9701/15290 [05:00<03:18, 28.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9704/15290 [05:00<03:15, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 63%|██████▎   | 9707/15290 [05:00<03:14, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9710/15290 [05:00<03:18, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9713/15290 [05:01<03:16, 28.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9716/15290 [05:01<03:19, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9719/15290 [05:01<03:16, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9722/15290 [05:01<03:21, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9725/15290 [05:01<03:26, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9728/15290 [05:01<03:22, 27.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9732/15290 [05:01<03:10, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9736/15290 [05:01<03:03, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9740/15290 [05:01<03:02, 30.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▎   | 9744/15290 [05:02<02:56, 31.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9748/15290 [05:02<02:57, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9752/15290 [05:02<03:02, 30.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9756/15290 [05:02<03:15, 28.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9759/15290 [05:02<03:13, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9763/15290 [05:02<03:07, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9766/15290 [05:02<03:07, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9769/15290 [05:02<03:21, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9772/15290 [05:03<03:19, 27.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9775/15290 [05:03<03:18, 27.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9779/15290 [05:03<03:09, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9783/15290 [05:03<03:06, 29.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9787/15290 [05:03<03:03, 30.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9791/15290 [05:03<02:59, 30.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9795/15290 [05:03<02:56, 31.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9799/15290 [05:03<02:56, 31.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9803/15290 [05:04<03:22, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9806/15290 [05:04<03:20, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9809/15290 [05:04<03:16, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9812/15290 [05:04<03:16, 27.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9816/15290 [05:04<03:07, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9820/15290 [05:04<03:03, 29.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9824/15290 [05:04<02:57, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9828/15290 [05:04<02:53, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9832/15290 [05:05<02:59, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9836/15290 [05:05<03:05, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9839/15290 [05:05<03:10, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9842/15290 [05:05<03:12, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9845/15290 [05:05<04:14, 21.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9848/15290 [05:05<04:39, 19.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9851/15290 [05:06<04:54, 18.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9854/15290 [05:06<04:39, 19.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9857/15290 [05:06<04:11, 21.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 64%|██████▍   | 9861/15290 [05:06<03:34, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9865/15290 [05:06<03:19, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9869/15290 [05:06<03:05, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9873/15290 [05:06<02:54, 31.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9877/15290 [05:06<02:56, 30.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9881/15290 [05:07<02:57, 30.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9885/15290 [05:07<02:45, 32.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9889/15290 [05:07<02:43, 32.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9893/15290 [05:07<02:44, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9897/15290 [05:07<02:50, 31.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9901/15290 [05:07<02:59, 30.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9905/15290 [05:07<03:01, 29.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9908/15290 [05:07<03:05, 28.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9911/15290 [05:07<03:07, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9914/15290 [05:08<03:05, 28.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9918/15290 [05:08<03:01, 29.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9922/15290 [05:08<02:57, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9926/15290 [05:08<02:54, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9930/15290 [05:08<02:53, 30.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9934/15290 [05:08<02:57, 30.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▍   | 9938/15290 [05:08<03:03, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9941/15290 [05:08<03:02, 29.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9945/15290 [05:09<02:59, 29.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9949/15290 [05:09<02:57, 30.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9953/15290 [05:09<03:00, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9957/15290 [05:09<03:00, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9960/15290 [05:09<03:03, 28.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9963/15290 [05:09<03:05, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9966/15290 [05:09<03:17, 27.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9969/15290 [05:09<03:18, 26.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9972/15290 [05:10<03:23, 26.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9975/15290 [05:10<03:24, 26.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9978/15290 [05:10<03:23, 26.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9981/15290 [05:10<03:16, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9984/15290 [05:10<03:14, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9987/15290 [05:10<03:16, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9990/15290 [05:10<03:37, 24.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9993/15290 [05:10<03:44, 23.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9996/15290 [05:11<03:40, 24.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 9999/15290 [05:11<03:35, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 10002/15290 [05:11<03:36, 24.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 10005/15290 [05:11<03:36, 24.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 10008/15290 [05:11<03:27, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 10011/15290 [05:11<03:24, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 65%|██████▌   | 10014/15290 [05:11<03:16, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10017/15290 [05:11<03:10, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10020/15290 [05:11<03:09, 27.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10023/15290 [05:12<03:07, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10026/15290 [05:12<03:09, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10029/15290 [05:12<03:12, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10032/15290 [05:12<03:15, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10035/15290 [05:12<03:12, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10038/15290 [05:12<03:12, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10041/15290 [05:12<03:18, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10044/15290 [05:12<03:17, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10047/15290 [05:12<03:14, 26.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10050/15290 [05:13<03:15, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10053/15290 [05:13<03:12, 27.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10056/15290 [05:13<03:16, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10059/15290 [05:13<03:16, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10062/15290 [05:13<03:17, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10065/15290 [05:13<03:18, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10068/15290 [05:13<03:18, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10071/15290 [05:13<03:20, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10074/15290 [05:13<03:24, 25.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10077/15290 [05:14<03:24, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10080/15290 [05:14<03:30, 24.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10083/15290 [05:14<03:27, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10086/15290 [05:14<03:24, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10089/15290 [05:14<03:22, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10092/15290 [05:14<03:16, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10095/15290 [05:14<03:18, 26.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10098/15290 [05:14<03:17, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10101/15290 [05:15<03:11, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10104/15290 [05:15<03:08, 27.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10107/15290 [05:15<03:06, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10110/15290 [05:15<03:03, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10113/15290 [05:15<03:07, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10116/15290 [05:15<03:04, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10119/15290 [05:15<03:01, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10122/15290 [05:15<03:03, 28.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10125/15290 [05:15<03:03, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▌   | 10129/15290 [05:16<02:57, 29.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10132/15290 [05:16<02:57, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10135/15290 [05:16<02:57, 28.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10138/15290 [05:16<02:57, 28.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10141/15290 [05:16<02:56, 29.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10144/15290 [05:16<03:01, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10148/15290 [05:16<02:55, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10151/15290 [05:16<02:59, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10154/15290 [05:16<02:58, 28.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10157/15290 [05:16<02:58, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10160/15290 [05:17<03:01, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10164/15290 [05:17<02:59, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 66%|██████▋   | 10167/15290 [05:17<02:58, 28.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10170/15290 [05:17<02:56, 28.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10173/15290 [05:17<02:56, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10176/15290 [05:17<02:55, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10179/15290 [05:17<02:58, 28.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10182/15290 [05:17<02:57, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10186/15290 [05:17<02:55, 29.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10190/15290 [05:18<02:53, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10194/15290 [05:18<02:52, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10198/15290 [05:18<02:51, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10202/15290 [05:18<02:50, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10206/15290 [05:18<02:46, 30.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10210/15290 [05:18<02:50, 29.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10213/15290 [05:18<02:53, 29.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10216/15290 [05:18<02:53, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10219/15290 [05:19<02:53, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10222/15290 [05:19<02:56, 28.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10225/15290 [05:19<02:56, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10228/15290 [05:19<02:55, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10232/15290 [05:19<02:51, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10235/15290 [05:19<02:54, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10238/15290 [05:19<02:59, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10241/15290 [05:19<02:57, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10244/15290 [05:19<02:55, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10247/15290 [05:20<02:56, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10250/15290 [05:20<02:56, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10253/15290 [05:20<02:55, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10256/15290 [05:20<02:56, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10259/15290 [05:20<02:53, 28.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10262/15290 [05:20<02:51, 29.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10265/15290 [05:20<02:55, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10268/15290 [05:20<02:55, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10271/15290 [05:20<02:56, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10274/15290 [05:21<02:54, 28.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10278/15290 [05:21<02:51, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10281/15290 [05:21<02:53, 28.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10284/15290 [05:21<02:56, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10288/15290 [05:21<02:51, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10292/15290 [05:21<02:50, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10295/15290 [05:21<02:56, 28.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10299/15290 [05:21<02:53, 28.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10302/15290 [05:21<02:54, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10305/15290 [05:22<02:54, 28.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10308/15290 [05:22<02:53, 28.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10311/15290 [05:22<03:01, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10314/15290 [05:22<03:01, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10317/15290 [05:22<02:58, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 67%|██████▋   | 10320/15290 [05:22<02:56, 28.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10323/15290 [05:22<02:59, 27.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10326/15290 [05:22<03:00, 27.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10329/15290 [05:22<03:04, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10333/15290 [05:23<02:55, 28.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10337/15290 [05:23<02:49, 29.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10340/15290 [05:23<02:50, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10343/15290 [05:23<02:52, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10346/15290 [05:23<03:01, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10349/15290 [05:23<03:14, 25.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10352/15290 [05:23<03:21, 24.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10355/15290 [05:23<03:25, 24.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10358/15290 [05:24<03:20, 24.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10361/15290 [05:24<03:17, 24.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10364/15290 [05:24<03:12, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10367/15290 [05:24<03:08, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10370/15290 [05:24<03:06, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10373/15290 [05:24<03:10, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10376/15290 [05:24<03:11, 25.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10379/15290 [05:24<03:10, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10382/15290 [05:24<03:05, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10385/15290 [05:25<02:59, 27.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10388/15290 [05:25<03:02, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10391/15290 [05:25<03:00, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10394/15290 [05:25<02:59, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10397/15290 [05:25<02:57, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10400/15290 [05:25<02:56, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10403/15290 [05:25<03:00, 27.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10406/15290 [05:25<03:01, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10409/15290 [05:25<03:00, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10412/15290 [05:26<02:55, 27.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10415/15290 [05:26<02:53, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10418/15290 [05:26<02:53, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10421/15290 [05:26<02:49, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10424/15290 [05:26<02:49, 28.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10427/15290 [05:26<02:48, 28.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10431/15290 [05:26<02:43, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10434/15290 [05:26<02:48, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10437/15290 [05:26<02:51, 28.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10440/15290 [05:27<02:55, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10443/15290 [05:27<03:01, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10447/15290 [05:27<02:57, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10450/15290 [05:27<02:57, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10454/15290 [05:27<02:50, 28.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10457/15290 [05:27<02:49, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10461/15290 [05:27<02:46, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10464/15290 [05:27<02:50, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10467/15290 [05:28<02:48, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10470/15290 [05:28<02:48, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 68%|██████▊   | 10473/15290 [05:28<02:50, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10476/15290 [05:28<02:48, 28.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10479/15290 [05:28<02:50, 28.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10483/15290 [05:28<02:46, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10486/15290 [05:28<02:46, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10489/15290 [05:28<02:44, 29.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10492/15290 [05:28<02:49, 28.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10495/15290 [05:28<02:49, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10498/15290 [05:29<02:49, 28.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10501/15290 [05:29<02:47, 28.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10504/15290 [05:29<02:49, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10508/15290 [05:29<02:43, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▊   | 10511/15290 [05:29<02:42, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10514/15290 [05:29<02:42, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10517/15290 [05:29<02:52, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10520/15290 [05:29<02:51, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10523/15290 [05:29<02:48, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10526/15290 [05:30<02:48, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10530/15290 [05:30<02:40, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10534/15290 [05:30<02:40, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10537/15290 [05:30<02:47, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10540/15290 [05:30<02:46, 28.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10544/15290 [05:30<02:41, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10547/15290 [05:30<02:41, 29.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10550/15290 [05:30<02:46, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10553/15290 [05:31<02:45, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10556/15290 [05:31<02:43, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10560/15290 [05:31<02:39, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10564/15290 [05:31<02:40, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10567/15290 [05:31<02:40, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10571/15290 [05:31<02:38, 29.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10574/15290 [05:31<02:38, 29.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10577/15290 [05:31<02:39, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10580/15290 [05:31<02:41, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10583/15290 [05:32<02:46, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10587/15290 [05:32<02:43, 28.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10591/15290 [05:32<02:39, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10594/15290 [05:32<02:38, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10597/15290 [05:32<02:39, 29.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10600/15290 [05:32<02:40, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10603/15290 [05:32<02:42, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10606/15290 [05:32<02:45, 28.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10609/15290 [05:32<02:45, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10612/15290 [05:33<02:44, 28.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10615/15290 [05:33<02:47, 27.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10618/15290 [05:33<02:48, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10621/15290 [05:33<02:49, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 69%|██████▉   | 10624/15290 [05:33<02:49, 27.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10627/15290 [05:33<02:48, 27.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10630/15290 [05:33<02:48, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10633/15290 [05:33<02:51, 27.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10636/15290 [05:33<02:49, 27.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10639/15290 [05:34<02:45, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10642/15290 [05:34<02:43, 28.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10645/15290 [05:34<02:46, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10648/15290 [05:34<02:45, 28.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10651/15290 [05:34<02:42, 28.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10654/15290 [05:34<02:42, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10657/15290 [05:34<02:58, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10660/15290 [05:34<03:18, 23.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10663/15290 [05:34<03:08, 24.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10666/15290 [05:35<02:59, 25.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10669/15290 [05:35<02:54, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10673/15290 [05:35<02:45, 27.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10677/15290 [05:35<02:41, 28.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10681/15290 [05:35<02:38, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10685/15290 [05:35<02:40, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10688/15290 [05:35<02:46, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10691/15290 [05:35<02:48, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10694/15290 [05:36<02:50, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10697/15290 [05:36<02:48, 27.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|██████▉   | 10700/15290 [05:36<02:49, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10703/15290 [05:36<02:52, 26.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10706/15290 [05:36<02:56, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10709/15290 [05:36<02:49, 27.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10712/15290 [05:36<02:48, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10716/15290 [05:36<02:40, 28.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10719/15290 [05:36<02:42, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10722/15290 [05:37<02:42, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10725/15290 [05:37<02:41, 28.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10729/15290 [05:37<02:38, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10733/15290 [05:37<02:35, 29.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10736/15290 [05:37<02:36, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10740/15290 [05:37<02:33, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10743/15290 [05:37<02:33, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10746/15290 [05:37<03:05, 24.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10749/15290 [05:38<03:09, 23.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10752/15290 [05:38<03:01, 24.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10755/15290 [05:38<02:55, 25.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10759/15290 [05:38<02:42, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10763/15290 [05:38<02:34, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10766/15290 [05:38<02:34, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10769/15290 [05:38<02:35, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10772/15290 [05:38<02:35, 29.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10775/15290 [05:38<02:36, 28.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 70%|███████   | 10778/15290 [05:39<02:36, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10781/15290 [05:39<02:36, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10784/15290 [05:39<02:35, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10787/15290 [05:39<02:35, 28.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10790/15290 [05:39<02:42, 27.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10793/15290 [05:39<02:39, 28.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10797/15290 [05:39<02:33, 29.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10800/15290 [05:39<02:47, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10803/15290 [05:39<02:47, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10806/15290 [05:40<02:49, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10809/15290 [05:40<02:47, 26.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10812/15290 [05:40<02:45, 27.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10816/15290 [05:40<02:37, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10819/15290 [05:40<02:40, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10822/15290 [05:40<02:39, 27.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10825/15290 [05:40<02:41, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10828/15290 [05:40<02:42, 27.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10831/15290 [05:40<02:44, 27.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10834/15290 [05:41<02:43, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10837/15290 [05:41<02:41, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10840/15290 [05:41<02:47, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10843/15290 [05:41<02:46, 26.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10846/15290 [05:41<02:45, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10849/15290 [05:41<02:40, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10852/15290 [05:41<02:41, 27.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10855/15290 [05:41<02:41, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10858/15290 [05:41<02:38, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10861/15290 [05:42<02:41, 27.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10864/15290 [05:42<02:37, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10867/15290 [05:42<02:42, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10870/15290 [05:42<02:40, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10874/15290 [05:42<02:36, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10877/15290 [05:42<02:36, 28.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10881/15290 [05:42<02:31, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10884/15290 [05:42<02:30, 29.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10888/15290 [05:43<02:26, 29.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████   | 10892/15290 [05:43<02:23, 30.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10896/15290 [05:43<02:26, 30.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10900/15290 [05:43<02:28, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10903/15290 [05:43<02:29, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10907/15290 [05:43<02:26, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10911/15290 [05:43<02:24, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10915/15290 [05:43<02:27, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10918/15290 [05:44<02:30, 28.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10921/15290 [05:44<02:33, 28.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10924/15290 [05:44<02:32, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10927/15290 [05:44<02:34, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 71%|███████▏  | 10931/15290 [05:44<02:30, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10934/15290 [05:44<02:30, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10937/15290 [05:44<02:29, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10941/15290 [05:44<02:28, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10944/15290 [05:44<02:30, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10947/15290 [05:45<02:33, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10951/15290 [05:45<02:27, 29.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10954/15290 [05:45<02:29, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10957/15290 [05:45<02:33, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10960/15290 [05:45<02:32, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10964/15290 [05:45<02:26, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10967/15290 [05:45<02:30, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10970/15290 [05:45<02:29, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10974/15290 [05:45<02:25, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10977/15290 [05:46<02:27, 29.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10980/15290 [05:46<02:27, 29.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10984/15290 [05:46<02:20, 30.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10988/15290 [05:46<02:22, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10992/15290 [05:46<02:25, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 10996/15290 [05:46<02:23, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11000/15290 [05:46<02:23, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11003/15290 [05:46<02:24, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11006/15290 [05:47<02:25, 29.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11009/15290 [05:47<02:34, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11013/15290 [05:47<02:30, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11017/15290 [05:47<02:26, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11020/15290 [05:47<02:26, 29.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11024/15290 [05:47<02:23, 29.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11027/15290 [05:47<02:24, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11030/15290 [05:47<02:32, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11033/15290 [05:47<02:33, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11036/15290 [05:48<02:33, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11039/15290 [05:48<02:32, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11043/15290 [05:48<02:27, 28.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11046/15290 [05:48<02:29, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11049/15290 [05:48<02:30, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11052/15290 [05:48<02:32, 27.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11055/15290 [05:48<02:40, 26.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11058/15290 [05:48<02:36, 27.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11061/15290 [05:49<02:37, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11064/15290 [05:49<02:38, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11067/15290 [05:49<02:34, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11071/15290 [05:49<02:26, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11074/15290 [05:49<02:30, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11077/15290 [05:49<02:28, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11080/15290 [05:49<02:33, 27.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 72%|███████▏  | 11083/15290 [05:49<02:36, 26.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11086/15290 [05:49<02:33, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11089/15290 [05:50<02:35, 27.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11092/15290 [05:50<02:39, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11095/15290 [05:50<02:36, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11099/15290 [05:50<02:29, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11102/15290 [05:50<02:28, 28.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11105/15290 [05:50<02:28, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11108/15290 [05:50<02:27, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11111/15290 [05:50<02:30, 27.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11114/15290 [05:50<02:33, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11117/15290 [05:51<02:33, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11120/15290 [05:51<02:31, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11123/15290 [05:51<02:30, 27.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11126/15290 [05:51<02:28, 28.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11129/15290 [05:51<02:26, 28.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11132/15290 [05:51<02:30, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11135/15290 [05:51<02:30, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11139/15290 [05:51<02:26, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11142/15290 [05:51<02:28, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11145/15290 [05:52<02:30, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11148/15290 [05:52<02:31, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11151/15290 [05:52<02:28, 27.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11154/15290 [05:52<02:27, 28.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11157/15290 [05:52<02:26, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11160/15290 [05:52<02:27, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11163/15290 [05:52<02:29, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11166/15290 [05:52<02:30, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11169/15290 [05:52<02:29, 27.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11172/15290 [05:53<02:31, 27.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11175/15290 [05:53<02:28, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11179/15290 [05:53<02:24, 28.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11183/15290 [05:53<02:18, 29.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11186/15290 [05:53<02:18, 29.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11189/15290 [05:53<02:19, 29.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11192/15290 [05:53<02:19, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11195/15290 [05:53<02:24, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11198/15290 [05:53<02:24, 28.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11202/15290 [05:54<02:18, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11206/15290 [05:54<02:16, 29.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11210/15290 [05:54<02:14, 30.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11214/15290 [05:54<02:13, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11218/15290 [05:54<02:14, 30.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11222/15290 [05:54<02:16, 29.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11225/15290 [05:54<02:22, 28.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11228/15290 [05:54<02:22, 28.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11231/15290 [05:55<02:25, 27.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11234/15290 [05:55<02:26, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 73%|███████▎  | 11237/15290 [05:55<02:24, 27.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11240/15290 [05:55<02:27, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11244/15290 [05:55<02:21, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11247/15290 [05:55<02:21, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11250/15290 [05:55<02:21, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11253/15290 [05:55<02:34, 26.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11256/15290 [05:55<02:41, 25.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11259/15290 [05:56<02:46, 24.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11262/15290 [05:56<03:02, 22.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11265/15290 [05:56<03:13, 20.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11268/15290 [05:56<02:58, 22.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11272/15290 [05:56<02:38, 25.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▎  | 11275/15290 [05:56<02:35, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11278/15290 [05:56<02:30, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11281/15290 [05:57<02:31, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11284/15290 [05:57<02:28, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11287/15290 [05:57<02:26, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11290/15290 [05:57<02:29, 26.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11293/15290 [05:57<02:34, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11296/15290 [05:57<02:37, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11299/15290 [05:57<02:50, 23.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11302/15290 [05:57<02:40, 24.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11305/15290 [05:57<02:34, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11308/15290 [05:58<02:52, 23.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11311/15290 [05:58<03:58, 16.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11313/15290 [05:58<04:23, 15.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11315/15290 [05:58<04:23, 15.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11319/15290 [05:58<03:28, 19.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11323/15290 [05:58<02:55, 22.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11326/15290 [05:59<02:49, 23.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11329/15290 [05:59<02:46, 23.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11332/15290 [05:59<02:46, 23.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11335/15290 [05:59<02:44, 24.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11338/15290 [05:59<02:41, 24.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11341/15290 [05:59<02:39, 24.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11344/15290 [05:59<02:42, 24.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11347/15290 [05:59<02:42, 24.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11350/15290 [06:00<02:36, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11353/15290 [06:00<02:35, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11356/15290 [06:00<02:28, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11359/15290 [06:00<02:27, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11362/15290 [06:00<02:22, 27.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11366/15290 [06:00<02:16, 28.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11370/15290 [06:00<02:11, 29.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11373/15290 [06:00<02:12, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11376/15290 [06:00<02:15, 28.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11379/15290 [06:01<02:16, 28.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11382/15290 [06:01<02:19, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11385/15290 [06:01<02:17, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 74%|███████▍  | 11389/15290 [06:01<02:12, 29.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11392/15290 [06:01<02:13, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11395/15290 [06:01<02:15, 28.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11398/15290 [06:01<02:24, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11401/15290 [06:01<02:24, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11405/15290 [06:01<02:18, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11408/15290 [06:02<02:26, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11411/15290 [06:02<02:44, 23.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11414/15290 [06:02<02:44, 23.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11417/15290 [06:02<02:44, 23.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11420/15290 [06:02<02:37, 24.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11424/15290 [06:02<02:26, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11427/15290 [06:02<02:23, 26.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11430/15290 [06:02<02:19, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11434/15290 [06:03<02:15, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11437/15290 [06:03<02:19, 27.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11440/15290 [06:03<02:18, 27.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11443/15290 [06:03<02:17, 27.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11446/15290 [06:03<02:16, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11449/15290 [06:03<02:15, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11452/15290 [06:03<02:16, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11455/15290 [06:03<02:17, 27.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11458/15290 [06:03<02:21, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11461/15290 [06:04<02:20, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11464/15290 [06:04<02:20, 27.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▍  | 11467/15290 [06:04<02:16, 27.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11470/15290 [06:04<02:16, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11473/15290 [06:04<02:17, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11476/15290 [06:04<02:18, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11479/15290 [06:04<02:16, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11482/15290 [06:04<02:19, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11485/15290 [06:04<02:20, 27.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11488/15290 [06:05<02:17, 27.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11491/15290 [06:05<02:16, 27.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11494/15290 [06:05<02:19, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11497/15290 [06:05<02:16, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11500/15290 [06:05<02:16, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11503/15290 [06:05<02:17, 27.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11507/15290 [06:05<02:11, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11510/15290 [06:05<02:12, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11513/15290 [06:05<02:13, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11516/15290 [06:06<02:14, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11519/15290 [06:06<02:17, 27.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11522/15290 [06:06<02:15, 27.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11526/15290 [06:06<02:10, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11530/15290 [06:06<02:06, 29.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11533/15290 [06:06<02:24, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11536/15290 [06:06<02:23, 26.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11539/15290 [06:06<02:19, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 75%|███████▌  | 11543/15290 [06:07<02:12, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11547/15290 [06:07<02:08, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11550/15290 [06:07<02:09, 28.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11553/15290 [06:07<02:12, 28.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11556/15290 [06:07<02:10, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11559/15290 [06:07<02:15, 27.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11562/15290 [06:07<02:13, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11565/15290 [06:07<02:13, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11568/15290 [06:07<02:16, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11571/15290 [06:08<02:20, 26.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11574/15290 [06:08<02:25, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11577/15290 [06:08<02:23, 25.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11580/15290 [06:08<02:24, 25.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11583/15290 [06:08<02:25, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11586/15290 [06:08<02:27, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11589/15290 [06:08<02:21, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11592/15290 [06:08<02:17, 26.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11595/15290 [06:08<02:16, 27.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11598/15290 [06:09<02:17, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11601/15290 [06:09<02:19, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11604/15290 [06:09<02:19, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11608/15290 [06:09<02:11, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11611/15290 [06:09<02:08, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11614/15290 [06:09<02:11, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11617/15290 [06:09<02:10, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11620/15290 [06:09<02:10, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11623/15290 [06:09<02:08, 28.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11626/15290 [06:10<02:08, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11629/15290 [06:10<02:08, 28.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11632/15290 [06:10<02:10, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11635/15290 [06:10<02:13, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11638/15290 [06:10<02:11, 27.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11641/15290 [06:10<02:16, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11644/15290 [06:10<02:18, 26.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11647/15290 [06:10<02:19, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11650/15290 [06:10<02:16, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11653/15290 [06:11<02:14, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▌  | 11656/15290 [06:11<02:14, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11659/15290 [06:11<02:15, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11662/15290 [06:11<02:14, 26.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11665/15290 [06:11<02:10, 27.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11668/15290 [06:11<02:14, 26.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11671/15290 [06:11<02:14, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11674/15290 [06:11<02:15, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11677/15290 [06:11<02:11, 27.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11680/15290 [06:12<02:10, 27.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11683/15290 [06:12<02:11, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11686/15290 [06:12<02:20, 25.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11689/15290 [06:12<02:19, 25.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11692/15290 [06:12<02:16, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 76%|███████▋  | 11695/15290 [06:12<02:12, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11698/15290 [06:12<02:09, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11701/15290 [06:12<02:10, 27.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11704/15290 [06:12<02:14, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11707/15290 [06:13<02:14, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11710/15290 [06:13<02:19, 25.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11713/15290 [06:13<02:14, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11716/15290 [06:13<02:18, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11719/15290 [06:13<02:18, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11722/15290 [06:13<02:16, 26.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11725/15290 [06:13<02:14, 26.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11728/15290 [06:13<02:13, 26.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11731/15290 [06:14<02:13, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11734/15290 [06:14<02:13, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11737/15290 [06:14<02:15, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11740/15290 [06:14<02:20, 25.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11743/15290 [06:14<02:18, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11746/15290 [06:14<02:12, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11749/15290 [06:14<02:15, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11752/15290 [06:14<02:16, 25.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11755/15290 [06:14<02:12, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11758/15290 [06:15<02:12, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11761/15290 [06:15<02:12, 26.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11764/15290 [06:15<02:09, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11767/15290 [06:15<02:07, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11770/15290 [06:15<02:07, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11773/15290 [06:15<02:13, 26.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11776/15290 [06:15<02:15, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11779/15290 [06:15<02:14, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11783/15290 [06:15<02:06, 27.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11786/15290 [06:16<02:05, 27.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11789/15290 [06:16<02:04, 28.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11792/15290 [06:16<02:07, 27.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11795/15290 [06:16<02:06, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11798/15290 [06:16<02:08, 27.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11801/15290 [06:16<02:11, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11804/15290 [06:16<02:09, 26.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11808/15290 [06:16<02:03, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11811/15290 [06:16<02:03, 28.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11814/15290 [06:17<02:02, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11817/15290 [06:17<02:04, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11820/15290 [06:17<02:03, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11823/15290 [06:17<02:07, 27.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11826/15290 [06:17<02:08, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11829/15290 [06:17<02:05, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11832/15290 [06:17<02:06, 27.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11835/15290 [06:17<02:10, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11839/15290 [06:17<02:02, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11843/15290 [06:18<01:59, 28.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11846/15290 [06:18<02:01, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 77%|███████▋  | 11849/15290 [06:18<02:04, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11852/15290 [06:18<02:05, 27.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11855/15290 [06:18<02:07, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11858/15290 [06:18<02:04, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11861/15290 [06:18<02:05, 27.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11864/15290 [06:18<02:09, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11867/15290 [06:19<02:05, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11870/15290 [06:19<02:03, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11873/15290 [06:19<02:05, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11876/15290 [06:19<02:03, 27.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11879/15290 [06:19<02:08, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11882/15290 [06:19<02:06, 26.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11885/15290 [06:19<02:05, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11888/15290 [06:19<02:06, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11891/15290 [06:19<02:09, 26.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11894/15290 [06:20<02:08, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11897/15290 [06:20<02:08, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11900/15290 [06:20<02:05, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11903/15290 [06:20<02:31, 22.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11906/15290 [06:20<02:23, 23.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11909/15290 [06:20<02:16, 24.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11912/15290 [06:20<02:14, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11915/15290 [06:20<02:10, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11918/15290 [06:20<02:05, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11921/15290 [06:21<02:05, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11924/15290 [06:21<02:04, 27.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11927/15290 [06:21<02:04, 27.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11931/15290 [06:21<01:59, 28.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11934/15290 [06:21<02:02, 27.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11937/15290 [06:21<01:59, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11940/15290 [06:21<01:57, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11943/15290 [06:21<02:00, 27.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11947/15290 [06:21<01:56, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11950/15290 [06:22<01:55, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11953/15290 [06:22<01:59, 27.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11956/15290 [06:22<02:00, 27.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11959/15290 [06:22<02:03, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11962/15290 [06:22<02:04, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11965/15290 [06:22<02:04, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11968/15290 [06:22<02:03, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11971/15290 [06:22<02:06, 26.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11974/15290 [06:23<02:09, 25.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11977/15290 [06:23<02:10, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11980/15290 [06:23<02:06, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11983/15290 [06:23<02:01, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11986/15290 [06:23<02:01, 27.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11989/15290 [06:23<02:03, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11992/15290 [06:23<02:00, 27.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11995/15290 [06:23<01:57, 28.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 11998/15290 [06:23<02:03, 26.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 78%|███████▊  | 12001/15290 [06:24<02:05, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12004/15290 [06:24<02:01, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12007/15290 [06:24<01:59, 27.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12010/15290 [06:24<01:57, 27.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12014/15290 [06:24<01:52, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12017/15290 [06:24<01:55, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12020/15290 [06:24<01:55, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12023/15290 [06:24<01:53, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12026/15290 [06:24<01:54, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12029/15290 [06:25<01:57, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12032/15290 [06:25<02:00, 27.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12035/15290 [06:25<01:57, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▊  | 12038/15290 [06:25<01:58, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12041/15290 [06:25<01:58, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12044/15290 [06:25<01:57, 27.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12047/15290 [06:25<01:57, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12050/15290 [06:25<01:57, 27.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12053/15290 [06:25<01:57, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12056/15290 [06:25<01:57, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12059/15290 [06:26<01:58, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12062/15290 [06:26<02:03, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12065/15290 [06:26<02:06, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12068/15290 [06:26<02:05, 25.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12071/15290 [06:26<02:02, 26.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12074/15290 [06:26<02:02, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12077/15290 [06:26<01:59, 26.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12080/15290 [06:26<02:01, 26.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12083/15290 [06:27<02:02, 26.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12086/15290 [06:27<01:59, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12089/15290 [06:27<01:59, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12092/15290 [06:27<02:01, 26.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12095/15290 [06:27<02:00, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12099/15290 [06:27<01:55, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12102/15290 [06:27<01:52, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12105/15290 [06:27<01:56, 27.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12108/15290 [06:27<01:56, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12111/15290 [06:28<01:53, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12114/15290 [06:28<01:52, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12117/15290 [06:28<01:52, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12120/15290 [06:28<01:54, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12123/15290 [06:28<01:55, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12126/15290 [06:28<01:54, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12129/15290 [06:28<01:59, 26.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12132/15290 [06:28<02:13, 23.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12135/15290 [06:28<02:12, 23.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12138/15290 [06:29<02:08, 24.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12141/15290 [06:29<02:04, 25.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12144/15290 [06:29<02:06, 24.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12147/15290 [06:29<02:00, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12150/15290 [06:29<02:04, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 79%|███████▉  | 12153/15290 [06:29<01:58, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12156/15290 [06:29<02:01, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12159/15290 [06:29<02:05, 24.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12162/15290 [06:30<02:02, 25.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12165/15290 [06:30<02:01, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12168/15290 [06:30<02:05, 24.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12171/15290 [06:30<02:13, 23.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12174/15290 [06:30<02:12, 23.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12177/15290 [06:30<02:09, 23.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12180/15290 [06:30<02:07, 24.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12183/15290 [06:30<02:06, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12186/15290 [06:31<02:04, 25.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12189/15290 [06:31<01:59, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12192/15290 [06:31<01:55, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12195/15290 [06:31<01:55, 26.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12198/15290 [06:31<01:51, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12201/15290 [06:31<01:54, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12204/15290 [06:31<01:55, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12207/15290 [06:31<01:55, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12210/15290 [06:31<01:55, 26.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12213/15290 [06:32<01:57, 26.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12216/15290 [06:32<01:58, 25.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12219/15290 [06:32<01:55, 26.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12222/15290 [06:32<01:54, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12225/15290 [06:32<01:56, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12228/15290 [06:32<01:56, 26.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|███████▉  | 12231/15290 [06:32<01:59, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12234/15290 [06:32<01:57, 25.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12237/15290 [06:32<01:55, 26.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12240/15290 [06:33<01:55, 26.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12243/15290 [06:33<01:58, 25.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12246/15290 [06:33<01:54, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12249/15290 [06:33<01:54, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12252/15290 [06:33<01:52, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12255/15290 [06:33<01:55, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12258/15290 [06:33<01:53, 26.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12261/15290 [06:33<02:01, 25.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12264/15290 [06:33<02:01, 24.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12267/15290 [06:34<01:55, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12270/15290 [06:34<01:52, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12273/15290 [06:34<01:49, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12276/15290 [06:34<01:48, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12279/15290 [06:34<01:48, 27.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12282/15290 [06:34<01:50, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12285/15290 [06:34<01:51, 27.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12288/15290 [06:34<01:49, 27.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12291/15290 [06:34<01:53, 26.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12294/15290 [06:35<01:54, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12297/15290 [06:35<01:54, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12300/15290 [06:35<01:50, 26.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12303/15290 [06:35<01:51, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 80%|████████  | 12306/15290 [06:35<01:51, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12309/15290 [06:35<01:52, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12312/15290 [06:35<01:51, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12315/15290 [06:35<01:50, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12318/15290 [06:35<01:49, 27.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12321/15290 [06:36<01:47, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12324/15290 [06:36<01:48, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12327/15290 [06:36<01:48, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12330/15290 [06:36<01:52, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12333/15290 [06:36<01:52, 26.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12336/15290 [06:36<01:50, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12339/15290 [06:36<01:55, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12342/15290 [06:36<01:55, 25.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12345/15290 [06:36<01:52, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12348/15290 [06:37<01:52, 26.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12351/15290 [06:37<01:51, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12354/15290 [06:37<01:55, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12357/15290 [06:37<01:55, 25.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12360/15290 [06:37<01:54, 25.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12363/15290 [06:37<01:52, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12366/15290 [06:37<01:52, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12369/15290 [06:37<01:51, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12372/15290 [06:38<01:51, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12375/15290 [06:38<01:51, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12378/15290 [06:38<01:53, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12381/15290 [06:38<01:49, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12384/15290 [06:38<01:50, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12387/15290 [06:38<01:47, 27.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12390/15290 [06:38<01:50, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12393/15290 [06:38<01:51, 26.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12396/15290 [06:38<01:52, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12399/15290 [06:39<01:49, 26.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12402/15290 [06:39<01:51, 25.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12405/15290 [06:39<01:53, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12408/15290 [06:39<01:53, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12411/15290 [06:39<01:51, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12414/15290 [06:39<01:51, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12417/15290 [06:39<01:47, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12420/15290 [06:39<01:49, 26.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████  | 12423/15290 [06:40<01:53, 25.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12426/15290 [06:40<02:00, 23.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12429/15290 [06:40<01:56, 24.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12432/15290 [06:40<01:53, 25.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12435/15290 [06:40<02:08, 22.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12438/15290 [06:40<02:04, 22.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12441/15290 [06:40<02:02, 23.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12444/15290 [06:40<01:57, 24.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12447/15290 [06:41<01:56, 24.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12450/15290 [06:41<01:53, 25.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12453/15290 [06:41<01:50, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12456/15290 [06:41<01:47, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 81%|████████▏ | 12459/15290 [06:41<01:44, 27.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12462/15290 [06:41<01:44, 27.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12465/15290 [06:41<01:43, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12468/15290 [06:41<01:43, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12471/15290 [06:41<01:43, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12474/15290 [06:42<01:43, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12477/15290 [06:42<01:41, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12480/15290 [06:42<01:42, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12483/15290 [06:42<01:42, 27.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12486/15290 [06:42<01:42, 27.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12489/15290 [06:42<01:45, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12492/15290 [06:42<01:44, 26.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12495/15290 [06:42<01:42, 27.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12498/15290 [06:42<01:45, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12501/15290 [06:43<01:44, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12504/15290 [06:43<01:43, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12507/15290 [06:43<01:41, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12510/15290 [06:43<01:40, 27.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12513/15290 [06:43<01:41, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12516/15290 [06:43<01:42, 26.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12519/15290 [06:43<01:45, 26.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12522/15290 [06:43<01:54, 24.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12525/15290 [06:43<02:02, 22.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12528/15290 [06:44<01:58, 23.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12531/15290 [06:44<01:55, 23.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12534/15290 [06:44<01:52, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12537/15290 [06:44<01:49, 25.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12540/15290 [06:44<01:56, 23.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12543/15290 [06:44<01:49, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12546/15290 [06:44<01:48, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12549/15290 [06:44<01:48, 25.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12552/15290 [06:45<01:48, 25.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12555/15290 [06:45<01:46, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12558/15290 [06:45<01:45, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12561/15290 [06:45<01:44, 26.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12564/15290 [06:45<01:44, 26.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12567/15290 [06:45<01:43, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12570/15290 [06:45<01:44, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12573/15290 [06:45<01:42, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12576/15290 [06:45<01:43, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12579/15290 [06:46<01:43, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12582/15290 [06:46<01:44, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12585/15290 [06:46<01:42, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12588/15290 [06:46<01:41, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12591/15290 [06:46<01:45, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12594/15290 [06:46<01:49, 24.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12597/15290 [06:46<01:45, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12600/15290 [06:46<01:48, 24.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12603/15290 [06:47<01:45, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12606/15290 [06:47<01:45, 25.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12609/15290 [06:47<01:44, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 82%|████████▏ | 12612/15290 [06:47<01:43, 25.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12615/15290 [06:47<01:42, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12618/15290 [06:47<01:40, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12621/15290 [06:47<01:39, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12624/15290 [06:47<01:39, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12627/15290 [06:47<01:40, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12630/15290 [06:48<01:41, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12633/15290 [06:48<01:39, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12636/15290 [06:48<01:41, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12639/15290 [06:48<01:42, 25.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12642/15290 [06:48<01:43, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12645/15290 [06:48<01:44, 25.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12648/15290 [06:48<01:42, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12651/15290 [06:48<01:43, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12654/15290 [06:48<01:44, 25.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12657/15290 [06:49<01:44, 25.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12660/15290 [06:49<01:42, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12663/15290 [06:49<01:40, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12666/15290 [06:49<01:43, 25.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12669/15290 [06:49<01:44, 25.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12672/15290 [06:49<01:44, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12675/15290 [06:49<01:45, 24.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12678/15290 [06:49<01:45, 24.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12681/15290 [06:50<01:41, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12684/15290 [06:50<01:38, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12687/15290 [06:50<01:37, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12690/15290 [06:50<01:34, 27.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12693/15290 [06:50<01:36, 27.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12696/15290 [06:50<01:36, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12699/15290 [06:50<01:38, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12702/15290 [06:50<01:39, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12705/15290 [06:50<01:37, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12708/15290 [06:51<01:36, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12711/15290 [06:51<01:36, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12714/15290 [06:51<01:35, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12717/15290 [06:51<01:34, 27.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12720/15290 [06:51<01:32, 27.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12723/15290 [06:51<01:32, 27.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12726/15290 [06:51<01:31, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12729/15290 [06:51<01:31, 27.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12732/15290 [06:51<01:33, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12735/15290 [06:52<01:33, 27.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12738/15290 [06:52<01:34, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12741/15290 [06:52<01:35, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12744/15290 [06:52<01:36, 26.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12747/15290 [06:52<01:35, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12750/15290 [06:52<01:36, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12753/15290 [06:52<01:35, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12756/15290 [06:52<01:36, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12759/15290 [06:52<01:35, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12762/15290 [06:53<01:33, 27.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 83%|████████▎ | 12765/15290 [06:53<01:32, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12768/15290 [06:53<01:33, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12771/15290 [06:53<01:33, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12774/15290 [06:53<01:34, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12777/15290 [06:53<01:34, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12780/15290 [06:53<01:33, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12783/15290 [06:53<01:34, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12786/15290 [06:53<01:34, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12789/15290 [06:54<01:33, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12792/15290 [06:54<01:32, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12795/15290 [06:54<01:34, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12798/15290 [06:54<01:36, 25.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12801/15290 [06:54<01:33, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▎ | 12804/15290 [06:54<01:33, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12807/15290 [06:54<01:33, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12810/15290 [06:54<01:33, 26.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12813/15290 [06:54<01:32, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12816/15290 [06:55<01:32, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12819/15290 [06:55<01:32, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12822/15290 [06:55<01:32, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12825/15290 [06:55<01:33, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12828/15290 [06:55<01:31, 26.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12831/15290 [06:55<01:31, 26.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12834/15290 [06:55<01:34, 26.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12837/15290 [06:55<01:35, 25.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12840/15290 [06:55<01:33, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12843/15290 [06:56<01:32, 26.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12846/15290 [06:56<01:32, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12849/15290 [06:56<01:30, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12852/15290 [06:56<01:31, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12855/15290 [06:56<01:33, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12858/15290 [06:56<01:34, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12861/15290 [06:56<01:32, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12864/15290 [06:56<01:31, 26.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12867/15290 [06:56<01:30, 26.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12870/15290 [06:57<01:29, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12873/15290 [06:57<01:29, 26.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12876/15290 [06:57<01:28, 27.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12879/15290 [06:57<01:30, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12882/15290 [06:57<01:31, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12885/15290 [06:57<01:32, 26.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12888/15290 [06:57<01:29, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12891/15290 [06:57<01:28, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12894/15290 [06:58<01:30, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12897/15290 [06:58<01:30, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12900/15290 [06:58<01:31, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12903/15290 [06:58<01:28, 27.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12906/15290 [06:58<01:28, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12909/15290 [06:58<01:29, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12912/15290 [06:58<01:29, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12915/15290 [06:58<01:29, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 84%|████████▍ | 12918/15290 [06:58<01:30, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12921/15290 [06:59<01:30, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12924/15290 [06:59<01:30, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12927/15290 [06:59<01:27, 26.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12930/15290 [06:59<01:29, 26.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12933/15290 [06:59<01:28, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12936/15290 [06:59<01:26, 27.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12939/15290 [06:59<01:26, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12942/15290 [06:59<01:29, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12945/15290 [06:59<01:33, 24.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12948/15290 [07:00<01:29, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12951/15290 [07:00<01:28, 26.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12954/15290 [07:00<01:29, 26.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12957/15290 [07:00<01:28, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12960/15290 [07:00<01:31, 25.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12963/15290 [07:00<01:29, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12966/15290 [07:00<01:27, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12969/15290 [07:00<01:26, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12972/15290 [07:00<01:26, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12975/15290 [07:01<01:24, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12978/15290 [07:01<01:28, 26.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12981/15290 [07:01<01:28, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12984/15290 [07:01<01:30, 25.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12987/15290 [07:01<01:38, 23.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12990/15290 [07:01<01:40, 22.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12993/15290 [07:01<01:38, 23.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▍ | 12996/15290 [07:01<01:35, 24.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 12999/15290 [07:02<01:33, 24.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13002/15290 [07:02<01:33, 24.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13005/15290 [07:02<01:30, 25.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13008/15290 [07:02<01:27, 25.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13011/15290 [07:02<01:25, 26.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13014/15290 [07:02<01:23, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13017/15290 [07:02<01:22, 27.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13020/15290 [07:02<01:22, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13023/15290 [07:02<01:24, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13026/15290 [07:03<01:21, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13029/15290 [07:03<01:23, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13032/15290 [07:03<01:28, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13035/15290 [07:03<01:30, 24.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13038/15290 [07:03<01:34, 23.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13041/15290 [07:03<01:32, 24.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13044/15290 [07:03<01:30, 24.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13047/15290 [07:03<01:29, 24.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13050/15290 [07:04<01:30, 24.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13053/15290 [07:04<01:30, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13056/15290 [07:04<01:27, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13059/15290 [07:04<01:25, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13062/15290 [07:04<01:24, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13065/15290 [07:04<01:26, 25.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13068/15290 [07:04<01:28, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 85%|████████▌ | 13071/15290 [07:04<01:28, 25.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13074/15290 [07:04<01:25, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13077/15290 [07:05<01:25, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13080/15290 [07:05<01:25, 25.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13083/15290 [07:05<01:24, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13086/15290 [07:05<01:25, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13089/15290 [07:05<01:28, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13092/15290 [07:05<01:30, 24.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13095/15290 [07:05<01:32, 23.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13098/15290 [07:05<01:31, 23.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13101/15290 [07:06<01:30, 24.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13104/15290 [07:06<01:27, 24.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13107/15290 [07:06<01:25, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13110/15290 [07:06<01:21, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13113/15290 [07:06<01:20, 27.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13116/15290 [07:06<01:23, 25.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13119/15290 [07:06<01:22, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13122/15290 [07:06<01:23, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13125/15290 [07:06<01:22, 26.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13128/15290 [07:07<01:23, 25.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13131/15290 [07:07<01:21, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13134/15290 [07:07<01:22, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13137/15290 [07:07<01:21, 26.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13140/15290 [07:07<01:21, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13143/15290 [07:07<01:19, 26.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13146/15290 [07:07<01:18, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13149/15290 [07:07<01:16, 27.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13152/15290 [07:07<01:19, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13155/15290 [07:08<01:19, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13158/15290 [07:08<01:20, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13161/15290 [07:08<01:19, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13164/15290 [07:08<01:20, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13167/15290 [07:08<01:20, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13170/15290 [07:08<01:21, 26.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13173/15290 [07:08<01:21, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13176/15290 [07:08<01:24, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13179/15290 [07:09<01:21, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13182/15290 [07:09<01:22, 25.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▌ | 13185/15290 [07:09<01:20, 26.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13188/15290 [07:09<01:19, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13191/15290 [07:09<01:21, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13194/15290 [07:09<01:18, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13197/15290 [07:09<01:18, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13200/15290 [07:09<01:19, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13203/15290 [07:09<01:19, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13206/15290 [07:10<01:17, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13209/15290 [07:10<01:17, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13212/15290 [07:10<01:18, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13215/15290 [07:10<01:15, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13218/15290 [07:10<01:17, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13221/15290 [07:10<01:20, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 86%|████████▋ | 13224/15290 [07:10<01:24, 24.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13227/15290 [07:10<01:24, 24.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13230/15290 [07:10<01:22, 24.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13233/15290 [07:11<01:21, 25.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13236/15290 [07:11<01:19, 25.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13239/15290 [07:11<01:19, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13242/15290 [07:11<01:18, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13245/15290 [07:11<01:18, 26.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13248/15290 [07:11<01:17, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13251/15290 [07:11<01:17, 26.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13254/15290 [07:11<01:18, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13257/15290 [07:12<01:17, 26.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13260/15290 [07:12<01:15, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13263/15290 [07:12<01:16, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13266/15290 [07:12<01:14, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13269/15290 [07:12<01:13, 27.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13272/15290 [07:12<01:13, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13275/15290 [07:12<01:11, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13278/15290 [07:12<01:13, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13281/15290 [07:12<01:14, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13284/15290 [07:13<01:15, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13287/15290 [07:13<01:16, 26.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13290/15290 [07:13<01:16, 26.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13293/15290 [07:13<01:17, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13296/15290 [07:13<01:16, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13299/15290 [07:13<01:15, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13302/15290 [07:13<01:15, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13305/15290 [07:13<01:14, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13308/15290 [07:13<01:17, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13311/15290 [07:14<01:16, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13314/15290 [07:14<01:14, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13317/15290 [07:14<01:16, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13320/15290 [07:14<01:16, 25.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13323/15290 [07:14<01:13, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13326/15290 [07:14<01:14, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13329/15290 [07:14<01:12, 26.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13332/15290 [07:14<01:13, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13335/15290 [07:14<01:17, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13338/15290 [07:15<01:18, 24.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13341/15290 [07:15<01:16, 25.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13344/15290 [07:15<01:14, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13347/15290 [07:15<01:12, 26.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13350/15290 [07:15<01:12, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13353/15290 [07:15<01:11, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13356/15290 [07:15<01:11, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13359/15290 [07:15<01:16, 25.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13362/15290 [07:15<01:13, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13365/15290 [07:16<01:12, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13368/15290 [07:16<01:11, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13371/15290 [07:16<01:11, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13374/15290 [07:16<01:11, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 87%|████████▋ | 13377/15290 [07:16<01:12, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13380/15290 [07:16<01:13, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13383/15290 [07:16<01:17, 24.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13386/15290 [07:16<01:19, 23.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13389/15290 [07:17<01:15, 25.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13392/15290 [07:17<01:14, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13395/15290 [07:17<01:16, 24.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13398/15290 [07:17<01:15, 24.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13401/15290 [07:17<01:14, 25.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13404/15290 [07:17<01:11, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13407/15290 [07:17<01:10, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13410/15290 [07:17<01:11, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13413/15290 [07:17<01:10, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13416/15290 [07:18<01:12, 25.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13419/15290 [07:18<01:14, 24.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13422/15290 [07:18<01:16, 24.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13425/15290 [07:18<01:16, 24.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13428/15290 [07:18<01:17, 24.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13431/15290 [07:18<01:14, 24.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13434/15290 [07:18<01:12, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13437/15290 [07:18<01:13, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13440/15290 [07:19<01:24, 21.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13443/15290 [07:19<01:31, 20.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13446/15290 [07:19<01:28, 20.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13449/15290 [07:19<01:21, 22.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13452/15290 [07:19<01:17, 23.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13455/15290 [07:19<01:17, 23.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13458/15290 [07:19<01:16, 23.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13461/15290 [07:20<01:15, 24.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13464/15290 [07:20<01:15, 24.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13467/15290 [07:20<01:15, 24.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13470/15290 [07:20<01:16, 23.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13473/15290 [07:20<01:16, 23.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13476/15290 [07:20<01:18, 23.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13479/15290 [07:20<01:17, 23.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13482/15290 [07:20<01:18, 23.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13485/15290 [07:21<01:16, 23.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13488/15290 [07:21<01:17, 23.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13491/15290 [07:21<01:16, 23.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13494/15290 [07:21<01:20, 22.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13497/15290 [07:21<01:21, 22.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13500/15290 [07:21<01:19, 22.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13503/15290 [07:21<01:16, 23.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13506/15290 [07:21<01:15, 23.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13509/15290 [07:22<01:15, 23.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13512/15290 [07:22<01:13, 24.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13515/15290 [07:22<01:10, 25.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13518/15290 [07:22<01:08, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13521/15290 [07:22<01:07, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13524/15290 [07:22<01:06, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13527/15290 [07:22<01:05, 26.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 88%|████████▊ | 13530/15290 [07:22<01:06, 26.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13533/15290 [07:22<01:05, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13536/15290 [07:23<01:06, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13539/15290 [07:23<01:07, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13542/15290 [07:23<01:07, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13545/15290 [07:23<01:06, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13548/15290 [07:23<01:05, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13551/15290 [07:23<01:06, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13554/15290 [07:23<01:04, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13557/15290 [07:23<01:05, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13560/15290 [07:24<01:06, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13563/15290 [07:24<01:05, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13566/15290 [07:24<01:04, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▊ | 13569/15290 [07:24<01:03, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13572/15290 [07:24<01:03, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13575/15290 [07:24<01:03, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13578/15290 [07:24<01:28, 19.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13581/15290 [07:24<01:20, 21.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13584/15290 [07:25<01:17, 22.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13587/15290 [07:25<01:12, 23.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13590/15290 [07:25<01:11, 23.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13593/15290 [07:25<01:09, 24.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13596/15290 [07:25<01:06, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13599/15290 [07:25<01:06, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13602/15290 [07:25<01:05, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13605/15290 [07:25<01:05, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13608/15290 [07:25<01:04, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13611/15290 [07:26<01:03, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13614/15290 [07:26<01:03, 26.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13617/15290 [07:26<01:02, 26.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13620/15290 [07:26<01:02, 26.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13623/15290 [07:26<01:02, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13626/15290 [07:26<01:02, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13629/15290 [07:26<01:02, 26.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13632/15290 [07:26<01:05, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13635/15290 [07:26<01:05, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13638/15290 [07:27<01:07, 24.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13641/15290 [07:27<01:06, 24.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13644/15290 [07:27<01:06, 24.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13647/15290 [07:27<01:06, 24.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13650/15290 [07:27<01:05, 25.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13653/15290 [07:27<01:03, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13656/15290 [07:27<01:03, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13659/15290 [07:27<01:03, 25.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13662/15290 [07:28<01:03, 25.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13665/15290 [07:28<01:03, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13668/15290 [07:28<01:04, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13671/15290 [07:28<01:03, 25.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13674/15290 [07:28<01:02, 25.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13677/15290 [07:28<01:02, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13680/15290 [07:28<01:01, 25.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 89%|████████▉ | 13683/15290 [07:28<01:01, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13686/15290 [07:28<01:01, 26.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13689/15290 [07:29<01:02, 25.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13692/15290 [07:29<01:02, 25.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13695/15290 [07:29<01:02, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13698/15290 [07:29<01:02, 25.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13701/15290 [07:29<01:01, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13704/15290 [07:29<01:02, 25.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13707/15290 [07:29<01:01, 25.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13710/15290 [07:29<01:02, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13713/15290 [07:30<01:01, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13716/15290 [07:30<01:01, 25.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13719/15290 [07:30<01:08, 22.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13722/15290 [07:30<01:05, 24.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13725/15290 [07:30<01:04, 24.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13728/15290 [07:30<01:02, 25.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13731/15290 [07:30<01:02, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13734/15290 [07:30<01:01, 25.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13737/15290 [07:31<01:01, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13740/15290 [07:31<01:02, 24.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13743/15290 [07:31<01:01, 25.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13746/15290 [07:31<01:01, 25.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13749/15290 [07:31<01:00, 25.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13752/15290 [07:31<00:59, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13755/15290 [07:31<00:59, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|████████▉ | 13758/15290 [07:31<01:02, 24.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13761/15290 [07:31<01:00, 25.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13764/15290 [07:32<00:58, 25.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13767/15290 [07:32<00:57, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13770/15290 [07:32<00:56, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13773/15290 [07:32<00:57, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13776/15290 [07:32<00:58, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13779/15290 [07:32<00:59, 25.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13782/15290 [07:32<00:59, 25.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13785/15290 [07:32<01:00, 24.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13788/15290 [07:33<00:59, 25.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13791/15290 [07:33<01:00, 24.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13794/15290 [07:33<01:00, 24.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13797/15290 [07:33<00:59, 24.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13800/15290 [07:33<00:59, 24.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13803/15290 [07:33<00:59, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13806/15290 [07:33<00:58, 25.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13809/15290 [07:33<00:58, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13812/15290 [07:33<00:57, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13815/15290 [07:34<00:57, 25.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13818/15290 [07:34<00:59, 24.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13821/15290 [07:34<00:58, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13824/15290 [07:34<00:59, 24.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13827/15290 [07:34<00:59, 24.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13830/15290 [07:34<01:01, 23.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13833/15290 [07:34<01:02, 23.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 90%|█████████ | 13836/15290 [07:34<01:02, 23.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13839/15290 [07:35<01:02, 23.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13842/15290 [07:35<01:02, 23.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13845/15290 [07:35<01:01, 23.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13848/15290 [07:35<01:01, 23.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13851/15290 [07:35<01:01, 23.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13854/15290 [07:35<01:01, 23.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13857/15290 [07:35<00:58, 24.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13860/15290 [07:35<00:56, 25.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13863/15290 [07:36<00:55, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13866/15290 [07:36<00:56, 25.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13869/15290 [07:36<00:57, 24.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13872/15290 [07:36<00:58, 24.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13875/15290 [07:36<00:59, 23.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13878/15290 [07:36<00:58, 24.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13881/15290 [07:36<01:00, 23.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13884/15290 [07:36<01:00, 23.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13887/15290 [07:37<01:01, 22.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13890/15290 [07:37<01:00, 23.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13893/15290 [07:37<01:00, 23.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13896/15290 [07:37<01:00, 22.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13899/15290 [07:37<01:02, 22.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13902/15290 [07:37<01:03, 21.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13905/15290 [07:37<01:03, 21.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13908/15290 [07:38<01:02, 22.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13911/15290 [07:38<01:00, 22.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13914/15290 [07:38<00:59, 23.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13917/15290 [07:38<01:02, 22.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13920/15290 [07:38<01:02, 21.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13923/15290 [07:38<01:01, 22.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13926/15290 [07:38<00:59, 22.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13929/15290 [07:38<00:57, 23.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13932/15290 [07:39<00:55, 24.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13935/15290 [07:39<00:54, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13938/15290 [07:39<00:54, 24.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13941/15290 [07:39<00:53, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13944/15290 [07:39<00:52, 25.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13947/15290 [07:39<00:52, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████ | 13950/15290 [07:39<00:54, 24.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13953/15290 [07:39<00:55, 24.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13956/15290 [07:40<00:53, 24.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13959/15290 [07:40<00:54, 24.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13962/15290 [07:40<00:58, 22.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13965/15290 [07:40<00:57, 22.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13968/15290 [07:40<00:58, 22.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13971/15290 [07:40<01:00, 21.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13974/15290 [07:40<01:01, 21.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13977/15290 [07:40<00:58, 22.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13980/15290 [07:41<00:55, 23.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13983/15290 [07:41<00:54, 24.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13986/15290 [07:41<00:53, 24.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 91%|█████████▏| 13989/15290 [07:41<00:53, 24.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 13992/15290 [07:41<00:51, 25.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 13995/15290 [07:41<00:49, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 13998/15290 [07:41<00:48, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14001/15290 [07:41<00:50, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14004/15290 [07:42<00:49, 25.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14007/15290 [07:42<00:49, 25.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14010/15290 [07:42<00:50, 25.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14013/15290 [07:42<00:49, 25.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14016/15290 [07:42<00:50, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14019/15290 [07:42<00:51, 24.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14022/15290 [07:42<00:51, 24.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14025/15290 [07:42<00:51, 24.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14028/15290 [07:43<00:50, 24.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14031/15290 [07:43<00:49, 25.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14034/15290 [07:43<00:50, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14037/15290 [07:43<00:49, 25.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14040/15290 [07:43<00:48, 25.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14043/15290 [07:43<00:49, 25.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14046/15290 [07:43<00:49, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14049/15290 [07:43<00:48, 25.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14052/15290 [07:43<00:49, 25.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14055/15290 [07:44<00:50, 24.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14058/15290 [07:44<00:50, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14061/15290 [07:44<00:50, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14064/15290 [07:44<00:49, 24.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14067/15290 [07:44<00:47, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14070/15290 [07:44<00:46, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14073/15290 [07:44<00:45, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14076/15290 [07:44<00:45, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14079/15290 [07:44<00:45, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14082/15290 [07:45<00:44, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14085/15290 [07:45<00:44, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14088/15290 [07:45<00:44, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14091/15290 [07:45<00:44, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14094/15290 [07:45<00:44, 26.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14097/15290 [07:45<00:43, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14100/15290 [07:45<00:43, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14103/15290 [07:45<00:44, 26.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14106/15290 [07:45<00:43, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14109/15290 [07:46<00:43, 27.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14112/15290 [07:46<00:43, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14115/15290 [07:46<00:42, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14118/15290 [07:46<00:41, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14121/15290 [07:46<00:41, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14124/15290 [07:46<00:42, 27.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14127/15290 [07:46<00:42, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14130/15290 [07:46<00:43, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14133/15290 [07:46<00:43, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14136/15290 [07:47<00:43, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14139/15290 [07:47<00:44, 25.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 92%|█████████▏| 14142/15290 [07:47<00:45, 25.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14145/15290 [07:47<00:45, 25.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14148/15290 [07:47<00:44, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14151/15290 [07:47<00:43, 25.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14154/15290 [07:47<00:46, 24.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14157/15290 [07:47<00:46, 24.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14160/15290 [07:48<00:44, 25.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14163/15290 [07:48<00:44, 25.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14166/15290 [07:48<00:43, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14169/15290 [07:48<00:45, 24.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14172/15290 [07:48<00:47, 23.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14175/15290 [07:48<00:50, 22.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14178/15290 [07:48<00:50, 22.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14181/15290 [07:48<00:48, 22.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14184/15290 [07:49<00:46, 23.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14187/15290 [07:49<00:45, 24.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14190/15290 [07:49<00:47, 23.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14193/15290 [07:49<00:46, 23.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14196/15290 [07:49<00:45, 23.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14199/15290 [07:49<00:44, 24.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14202/15290 [07:49<00:44, 24.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14205/15290 [07:49<00:45, 24.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14208/15290 [07:50<00:45, 23.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14211/15290 [07:50<00:43, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14214/15290 [07:50<00:43, 24.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14217/15290 [07:50<00:43, 24.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14220/15290 [07:50<00:43, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14223/15290 [07:50<00:43, 24.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14226/15290 [07:50<00:43, 24.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14229/15290 [07:50<00:44, 23.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14232/15290 [07:51<00:48, 21.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14235/15290 [07:51<00:46, 22.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14238/15290 [07:51<00:48, 21.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14241/15290 [07:51<00:49, 21.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14244/15290 [07:51<00:46, 22.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14247/15290 [07:51<00:46, 22.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14250/15290 [07:51<00:45, 22.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14253/15290 [07:52<00:46, 22.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14256/15290 [07:52<00:46, 22.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14259/15290 [07:52<00:44, 22.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14262/15290 [07:52<00:44, 23.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14265/15290 [07:52<00:43, 23.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14268/15290 [07:52<00:44, 23.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14271/15290 [07:52<00:45, 22.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14274/15290 [07:52<00:43, 23.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14277/15290 [07:53<00:42, 23.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14280/15290 [07:53<00:42, 23.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14283/15290 [07:53<00:41, 24.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14286/15290 [07:53<00:40, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14289/15290 [07:53<00:42, 23.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14292/15290 [07:53<00:43, 23.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 93%|█████████▎| 14295/15290 [07:53<00:42, 23.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14298/15290 [07:53<00:41, 23.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14301/15290 [07:54<00:40, 24.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14304/15290 [07:54<00:40, 24.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14307/15290 [07:54<00:38, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14310/15290 [07:54<00:36, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14313/15290 [07:54<00:36, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14316/15290 [07:54<00:35, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14319/15290 [07:54<00:35, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14322/15290 [07:54<00:35, 27.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14325/15290 [07:54<00:35, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14328/15290 [07:55<00:36, 26.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14331/15290 [07:55<00:36, 26.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▎| 14334/15290 [07:55<00:36, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14337/15290 [07:55<00:37, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14340/15290 [07:55<00:37, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14343/15290 [07:55<00:36, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14346/15290 [07:55<00:36, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14349/15290 [07:55<00:36, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14352/15290 [07:56<00:36, 25.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14355/15290 [07:56<00:36, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14358/15290 [07:56<00:36, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14361/15290 [07:56<00:36, 25.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14364/15290 [07:56<00:36, 25.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14367/15290 [07:56<00:35, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14370/15290 [07:56<00:35, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14373/15290 [07:56<00:35, 26.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14376/15290 [07:56<00:35, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14379/15290 [07:57<00:35, 25.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14382/15290 [07:57<00:34, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14385/15290 [07:57<00:34, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14388/15290 [07:57<00:34, 26.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14391/15290 [07:57<00:35, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14394/15290 [07:57<00:35, 25.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14397/15290 [07:57<00:35, 25.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14400/15290 [07:57<00:35, 25.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14403/15290 [07:57<00:34, 25.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14406/15290 [07:58<00:34, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14409/15290 [07:58<00:34, 25.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14412/15290 [07:58<00:33, 26.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14415/15290 [07:58<00:33, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14418/15290 [07:58<00:33, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14421/15290 [07:58<00:33, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14424/15290 [07:58<00:33, 26.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14427/15290 [07:58<00:33, 25.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14430/15290 [07:59<00:33, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14433/15290 [07:59<00:33, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14436/15290 [07:59<00:34, 24.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14439/15290 [07:59<00:33, 25.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14442/15290 [07:59<00:33, 25.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14445/15290 [07:59<00:34, 24.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 94%|█████████▍| 14448/15290 [07:59<00:33, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14451/15290 [07:59<00:33, 25.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14454/15290 [07:59<00:33, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14457/15290 [08:00<00:33, 25.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14460/15290 [08:00<00:32, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14463/15290 [08:00<00:31, 25.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14466/15290 [08:00<00:32, 25.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14469/15290 [08:00<00:31, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14472/15290 [08:00<00:31, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14475/15290 [08:00<00:31, 25.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14478/15290 [08:00<00:31, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14481/15290 [08:01<00:31, 25.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14484/15290 [08:01<00:30, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14487/15290 [08:01<00:31, 25.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14490/15290 [08:01<00:31, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14493/15290 [08:01<00:31, 25.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14496/15290 [08:01<00:31, 25.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14499/15290 [08:01<00:31, 24.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14502/15290 [08:01<00:31, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14505/15290 [08:02<00:32, 24.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14508/15290 [08:02<00:31, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14511/15290 [08:02<00:31, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14514/15290 [08:02<00:30, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14517/15290 [08:02<00:29, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14520/15290 [08:02<00:29, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▍| 14523/15290 [08:02<00:29, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14526/15290 [08:02<00:28, 26.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14529/15290 [08:02<00:28, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14532/15290 [08:03<00:28, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14535/15290 [08:03<00:28, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14538/15290 [08:03<00:28, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14541/15290 [08:03<00:29, 25.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14544/15290 [08:03<00:29, 25.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14547/15290 [08:03<00:28, 25.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14550/15290 [08:03<00:29, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14553/15290 [08:03<00:30, 23.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14556/15290 [08:03<00:30, 24.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14559/15290 [08:04<00:29, 24.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14562/15290 [08:04<00:28, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14565/15290 [08:04<00:28, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14568/15290 [08:04<00:28, 24.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14571/15290 [08:04<00:29, 24.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14574/15290 [08:04<00:29, 24.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14577/15290 [08:04<00:29, 23.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14580/15290 [08:04<00:29, 24.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14583/15290 [08:05<00:30, 23.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14586/15290 [08:05<00:30, 23.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14589/15290 [08:05<00:29, 23.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14592/15290 [08:05<00:29, 23.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14595/15290 [08:05<00:28, 24.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14598/15290 [08:05<00:28, 24.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 95%|█████████▌| 14601/15290 [08:05<00:28, 24.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14604/15290 [08:05<00:27, 24.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14607/15290 [08:06<00:28, 24.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14610/15290 [08:06<00:27, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14613/15290 [08:06<00:27, 24.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14616/15290 [08:06<00:26, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14619/15290 [08:06<00:26, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14622/15290 [08:06<00:26, 25.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14625/15290 [08:06<00:26, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14628/15290 [08:06<00:26, 25.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14631/15290 [08:07<00:26, 25.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14634/15290 [08:07<00:26, 25.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14637/15290 [08:07<00:25, 25.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14640/15290 [08:07<00:25, 25.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14643/15290 [08:07<00:25, 25.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14646/15290 [08:07<00:25, 25.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14649/15290 [08:07<00:26, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14652/15290 [08:07<00:25, 24.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14655/15290 [08:08<00:26, 23.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14658/15290 [08:08<00:25, 24.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14661/15290 [08:08<00:25, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14664/15290 [08:08<00:26, 24.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14667/15290 [08:08<00:25, 24.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14670/15290 [08:08<00:25, 23.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14673/15290 [08:08<00:25, 24.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14676/15290 [08:08<00:25, 24.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14679/15290 [08:08<00:24, 24.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14682/15290 [08:09<00:24, 24.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14685/15290 [08:09<00:24, 24.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14688/15290 [08:09<00:24, 24.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14691/15290 [08:09<00:24, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14694/15290 [08:09<00:24, 24.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14697/15290 [08:09<00:23, 24.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14700/15290 [08:09<00:23, 25.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14703/15290 [08:09<00:23, 24.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14706/15290 [08:10<00:24, 23.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14709/15290 [08:10<00:24, 23.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14712/15290 [08:10<00:23, 24.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▌| 14715/15290 [08:10<00:23, 24.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14718/15290 [08:10<00:24, 23.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14721/15290 [08:10<00:24, 23.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14724/15290 [08:10<00:23, 23.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14727/15290 [08:10<00:23, 24.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14730/15290 [08:11<00:23, 23.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14733/15290 [08:11<00:23, 24.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14736/15290 [08:11<00:23, 23.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14739/15290 [08:11<00:22, 24.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14742/15290 [08:11<00:21, 24.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14745/15290 [08:11<00:21, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14748/15290 [08:11<00:20, 26.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14751/15290 [08:11<00:20, 26.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 96%|█████████▋| 14754/15290 [08:12<00:22, 24.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14757/15290 [08:12<00:22, 23.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14760/15290 [08:12<00:22, 23.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14763/15290 [08:12<00:22, 23.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14766/15290 [08:12<00:22, 23.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14769/15290 [08:12<00:22, 23.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14772/15290 [08:12<00:24, 21.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14775/15290 [08:12<00:22, 22.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14778/15290 [08:13<00:22, 23.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14781/15290 [08:13<00:21, 24.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14784/15290 [08:13<00:20, 24.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14787/15290 [08:13<00:20, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14790/15290 [08:13<00:20, 24.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14793/15290 [08:13<00:19, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14796/15290 [08:13<00:19, 24.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14799/15290 [08:13<00:19, 24.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14802/15290 [08:14<00:19, 24.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14805/15290 [08:14<00:19, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14808/15290 [08:14<00:19, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14811/15290 [08:14<00:19, 24.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14814/15290 [08:14<00:18, 25.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14817/15290 [08:14<00:18, 25.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14820/15290 [08:14<00:18, 24.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14823/15290 [08:14<00:18, 25.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14826/15290 [08:15<00:18, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14829/15290 [08:15<00:18, 25.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14832/15290 [08:15<00:18, 25.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14835/15290 [08:15<00:18, 25.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14838/15290 [08:15<00:17, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14841/15290 [08:15<00:17, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14844/15290 [08:15<00:17, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14847/15290 [08:15<00:17, 25.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14850/15290 [08:15<00:17, 25.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14853/15290 [08:16<00:17, 24.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14856/15290 [08:16<00:17, 25.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14859/15290 [08:16<00:17, 25.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14862/15290 [08:16<00:16, 25.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14865/15290 [08:16<00:16, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14868/15290 [08:16<00:16, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14871/15290 [08:16<00:16, 25.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14874/15290 [08:16<00:16, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14877/15290 [08:17<00:16, 25.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14880/15290 [08:17<00:16, 25.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14883/15290 [08:17<00:15, 25.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14886/15290 [08:17<00:15, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14889/15290 [08:17<00:15, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14892/15290 [08:17<00:15, 25.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14895/15290 [08:17<00:15, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14898/15290 [08:17<00:15, 25.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14901/15290 [08:17<00:15, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14904/15290 [08:18<00:15, 25.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 97%|█████████▋| 14907/15290 [08:18<00:15, 25.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14910/15290 [08:18<00:14, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14913/15290 [08:18<00:14, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14916/15290 [08:18<00:14, 25.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14919/15290 [08:18<00:14, 26.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14922/15290 [08:18<00:14, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14925/15290 [08:18<00:14, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14928/15290 [08:19<00:14, 24.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14931/15290 [08:19<00:14, 25.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14934/15290 [08:19<00:14, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14937/15290 [08:19<00:14, 24.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14940/15290 [08:19<00:13, 25.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14943/15290 [08:19<00:13, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14946/15290 [08:19<00:13, 25.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14949/15290 [08:19<00:14, 23.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14952/15290 [08:20<00:15, 22.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14955/15290 [08:20<00:15, 22.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14958/15290 [08:20<00:14, 22.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14961/15290 [08:20<00:14, 22.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14964/15290 [08:20<00:14, 22.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14967/15290 [08:20<00:14, 22.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14970/15290 [08:20<00:14, 22.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14973/15290 [08:20<00:14, 22.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14976/15290 [08:21<00:14, 21.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14979/15290 [08:21<00:14, 21.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14982/15290 [08:21<00:14, 20.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14985/15290 [08:21<00:14, 21.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14988/15290 [08:21<00:14, 21.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14991/15290 [08:21<00:14, 20.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14994/15290 [08:21<00:13, 21.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 14997/15290 [08:22<00:14, 20.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15000/15290 [08:22<00:13, 21.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15003/15290 [08:22<00:13, 21.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15006/15290 [08:22<00:14, 19.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15008/15290 [08:22<00:14, 19.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15011/15290 [08:22<00:14, 19.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15014/15290 [08:22<00:13, 21.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15017/15290 [08:23<00:12, 21.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15020/15290 [08:23<00:12, 22.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15023/15290 [08:23<00:12, 22.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15026/15290 [08:23<00:11, 22.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15029/15290 [08:23<00:11, 22.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15032/15290 [08:23<00:10, 23.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15035/15290 [08:23<00:10, 23.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15038/15290 [08:23<00:10, 24.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15041/15290 [08:24<00:10, 24.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15044/15290 [08:24<00:09, 24.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15047/15290 [08:24<00:09, 25.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15050/15290 [08:24<00:09, 25.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15053/15290 [08:24<00:09, 25.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15056/15290 [08:24<00:09, 24.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 98%|█████████▊| 15059/15290 [08:24<00:09, 24.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15062/15290 [08:24<00:09, 23.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15065/15290 [08:25<00:09, 23.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15068/15290 [08:25<00:09, 23.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15071/15290 [08:25<00:09, 23.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15074/15290 [08:25<00:09, 23.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15077/15290 [08:25<00:09, 23.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15080/15290 [08:25<00:09, 23.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15083/15290 [08:25<00:09, 22.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15086/15290 [08:25<00:08, 22.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15089/15290 [08:26<00:09, 22.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15092/15290 [08:26<00:08, 22.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15095/15290 [08:26<00:09, 21.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▊| 15098/15290 [08:26<00:08, 22.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15101/15290 [08:26<00:08, 22.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15104/15290 [08:26<00:08, 22.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15107/15290 [08:26<00:08, 22.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15110/15290 [08:27<00:07, 23.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15113/15290 [08:27<00:07, 23.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15116/15290 [08:27<00:07, 23.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15119/15290 [08:27<00:07, 23.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15122/15290 [08:27<00:07, 23.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15125/15290 [08:27<00:07, 23.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15128/15290 [08:27<00:07, 22.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15131/15290 [08:27<00:06, 23.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15134/15290 [08:28<00:06, 23.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15137/15290 [08:28<00:06, 23.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15140/15290 [08:28<00:06, 24.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15143/15290 [08:28<00:06, 24.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15146/15290 [08:28<00:06, 23.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15149/15290 [08:28<00:05, 24.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15152/15290 [08:28<00:05, 23.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15155/15290 [08:28<00:05, 23.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15158/15290 [08:29<00:05, 24.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15161/15290 [08:29<00:05, 23.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15164/15290 [08:29<00:05, 24.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15167/15290 [08:29<00:04, 24.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15170/15290 [08:29<00:04, 24.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15173/15290 [08:29<00:04, 24.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15176/15290 [08:29<00:04, 24.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15179/15290 [08:29<00:04, 24.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15182/15290 [08:30<00:04, 24.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15185/15290 [08:30<00:04, 24.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15188/15290 [08:30<00:04, 24.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15191/15290 [08:30<00:04, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15194/15290 [08:30<00:03, 24.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15197/15290 [08:30<00:03, 24.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15200/15290 [08:30<00:03, 24.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15203/15290 [08:30<00:03, 23.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15206/15290 [08:31<00:03, 23.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15209/15290 [08:31<00:03, 24.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
 99%|█████████▉| 15212/15290 [08:31<00:03, 23.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15215/15290 [08:31<00:03, 24.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15218/15290 [08:31<00:02, 24.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15221/15290 [08:31<00:02, 24.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15224/15290 [08:31<00:02, 24.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15227/15290 [08:31<00:02, 24.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15230/15290 [08:32<00:02, 23.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15233/15290 [08:32<00:02, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15236/15290 [08:32<00:02, 24.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15239/15290 [08:32<00:02, 24.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15242/15290 [08:32<00:01, 24.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15245/15290 [08:32<00:01, 24.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15248/15290 [08:32<00:01, 24.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15251/15290 [08:32<00:01, 24.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15254/15290 [08:33<00:01, 23.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15257/15290 [08:33<00:01, 23.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15260/15290 [08:33<00:01, 23.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15263/15290 [08:33<00:01, 23.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15266/15290 [08:33<00:01, 23.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15269/15290 [08:33<00:00, 23.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15272/15290 [08:33<00:00, 23.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15275/15290 [08:33<00:00, 23.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15278/15290 [08:34<00:00, 23.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15281/15290 [08:34<00:00, 22.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15284/15290 [08:34<00:00, 22.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15287/15290 [08:34<00:00, 23.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
  df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|██████████| 15290/15290 [08:34<00:00, 29.71it/s]

#DATA MANGLING BEFORE TRAINING MODELS:
print("MODELS REPORT:")
print('Initial number of variables = {}'.format(len(model_X.columns)))
print("Initial distribution: ",sorted(Counter(model_Y).items()))


fraud_X_train = model_X.copy()
fraud_Y_train = model_Y.copy()
fraud_X_test = df_nlp_score.copy()
fraud_Y_test = nlp_target.copy()

#limiting words in training set:
if min_words > 0:
    print('Limiting training set to observations with minimum {} words'.format(min_words))
    model_to_limit = model_to_limit[model_to_limit>(min_words-1)]
    fraud_X_train = fraud_X_train[fraud_X_train.index.isin(model_to_limit.index)]
    fraud_Y_train = fraud_Y_train[fraud_Y_train.index.isin(fraud_X_train.index)]
    
#Limiting dictionary to fraud:
if fraud_only ==True:
    df_fraud_only = df_post_nlp[df_post_nlp[target_column_name]==1]
    limit_list = []
    for column in df_fraud_only.columns:
        if df_fraud_only[column].sum() == 0:
            limit_list.append(column)
    X_limited = fraud_X_train.drop(limit_list, axis=1)
    print('Number of columns after limiting = {}'.format(len(X_limited.columns)))
else:
    X_limited = fraud_X_train.copy()
    
#Cutting low count variables:
X_cut = X_limited.copy()
Y_cut = fraud_Y_train.copy()
if low_cut == True:
    cut_list = []
    for column in X_limited.columns:
        if X_limited[column].astype(bool).sum() < at_least:
            cut_list.append(column)
    X_cut = X_cut.drop(cut_list, axis=1)
    print('Number of columns after cutting = {}'.format(len(X_cut.columns)))

#Oversampling or not:
if oversample == True:
    print("Distribution before oversampling: ",sorted(Counter(fraud_Y_train).items()))
    sampling_list = list(Counter(fraud_Y_train).items())
    sample_strategy = {0: sampling_list[0][1], 1 : (round((sampling_list[0][1])/over_proportion))}
    ros = RandomOverSampler(random_state=0, sampling_strategy=sample_strategy)
    X_resampled, Y_resampled = ros.fit_resample(fraud_X_train, fraud_Y_train)
    print("Distribution after oversampling to {}%: {}".format((100/over_proportion),sorted(Counter(Y_resampled).items())))
else:
    print('Not applying oversampling. Your choice...')
    X_resampled = fraud_X_train.copy()
    Y_resampled = fraud_Y_train.copy()
    print(sorted(Counter(Y_resampled).items()))

#Choosing k-best variables:
if if_k_best == True:
    if how_much_var > len(X_resampled.columns):
        how_much_var = 'all'
        print("All {} variables selected!".format(len(X_resampled.columns)))
    if type(how_much_var) == int:
        print("Choosing best {} variables/words".format(how_much_var))
    k_best = SelectKBest(score_func=chi2,k=how_much_var)
    fit = k_best.fit(X_resampled, Y_resampled)
    new_X_train = fit.transform(X_resampled)
    new_X_test = fit.transform(fraud_X_test)
    new_Y_train = Y_resampled
    new_Y_test = fraud_Y_test
else:
    print("All {} variables selected!".format(len(X_resampled.columns)))
    new_X_train = X_resampled
    new_X_test = fraud_X_test
    new_Y_train = Y_resampled
    new_Y_test = fraud_Y_test

#MODEL TRAINING:
#1. Logistic Regression with or without optimized parameters:
if lr_search == True:
    grid_search_lr = GridSearchCV(LogisticRegression(),param_grid_lr,scoring=scoring_lr,cv=10)
    grid_search_lr.fit(new_X_train, new_Y_train)
    print('Best Parameters for Logistic Regression Model: ',grid_search_lr.best_params_)
    print('Best Score for Logistic Regression Model: ',grid_search_lr.best_score_)
    fraud_model_lr = LogisticRegression(**grid_search_lr.best_params_,max_iter=200000)
else:
    fraud_model_lr = LogisticRegression(C=lr_c,penalty=lr_penalty,max_iter=200000)
fraud_logreg = fraud_model_lr.fit(new_X_train, new_Y_train)
print("Finished training Logistic Regression model!")
#2. SVM with or without optimized parameters:
if svm_search == True:
    grid_search = GridSearchCV(SVC(random_state=42, probability=True), param_grid, scoring=scoring_svm, cv=3)
    grid_search.fit(new_X_train, new_Y_train)
    print('Best Parameters for SVM Model: ',grid_search.best_params_)
    print('Best Score for SVM Model: ',grid_search.best_score_)
    fraud_model_svm = SVC(**grid_search.best_params_,random_state=42,probability=True)
else:
    fraud_model_svm = SVC(C=svm_c,kernel=svm_kernel,gamma=svm_gamma,random_state=42,probability=True)
fraud_svm = fraud_model_svm.fit(new_X_train, new_Y_train)
print("Finished training SVM model!")

MODELS REPORT:
Initial number of variables = 15289
Initial distribution:  [(0, 8492), (1, 448)]
Distribution before oversampling:  [(0, 8492), (1, 448)]
Distribution after oversampling to 10.0%: [(0, 8492), (1, 849)]
Choosing best 5000 variables/words
Finished training Logistic Regression model!
Finished training SVM model!

#MODELS EVALUATION:
print('NLP MODELS EVALUATION:')
print("WARNING: The purpose of nlp scoring and subsequent models is to provide variables for futher modelling, this is just to ensure that text gave us some useful information in relation with final model's target value")
fraud_predictions_lr = fraud_logreg.predict(new_X_test) 
fraud_predictions_svm = fraud_svm.predict(new_X_test) 
acc_lr = accuracy_score(new_Y_test,fraud_predictions_lr)
acc_svm = accuracy_score(new_Y_test,fraud_predictions_svm)
prec_lr = precision_score(new_Y_test,fraud_predictions_lr)
prec_svm = precision_score(new_Y_test,fraud_predictions_svm)
recall_lr = recall_score(new_Y_test,fraud_predictions_lr)
recall_svm = recall_score(new_Y_test,fraud_predictions_svm)
f1_lr = f1_score(new_Y_test,fraud_predictions_lr)
f1_svm = f1_score(new_Y_test,fraud_predictions_svm)
roc_lr = roc_auc_score(new_Y_test,fraud_predictions_lr)
roc_svm = roc_auc_score(new_Y_test,fraud_predictions_svm)
print('Accuracy: Logistic Regression - ' + str(acc_lr*100) + '%, SVM - ' + str(acc_svm*100) + '%')
print('Precision: Logistic Regression - ' + str(prec_lr*100) + '%, SVM - ' + str(prec_svm*100) + '%')
print('Recall: Logistic Regression - ' + str(recall_lr*100) + '%, SVM - ' + str(recall_svm*100) + '%')
print('F1: Logistic Regression - ' + str(f1_lr*100) + '%, SVM - ' + str(f1_svm*100) + '%')
print('Area Under ROC: Logistic Regression - ' + str(roc_lr*100) + '%, SVM - ' + str(roc_svm*100) + '%')
conf_matrix_lr = confusion_matrix(fraud_Y_test,fraud_predictions_lr)
conf_matrix_svm = confusion_matrix(fraud_Y_test,fraud_predictions_svm)
confusion_matrix_df_lr = pd.DataFrame(conf_matrix_lr)
confusion_matrix_df_svm = pd.DataFrame(conf_matrix_svm)

#plotting confussion matrixes:
fig,axs = plt.subplots(nrows=1,ncols=2, figsize=(15,5))
plt.figure(figsize=(6, 6))
sns.heatmap(ax=axs[0], data=confusion_matrix_df_lr, annot=True, fmt="d", cmap='Blues')
axs[0].set_title('Confusion Matrix for NLP Logistic Regression')
axs[0].set(xlabel='Predicted',ylabel='Actual')
plt.figure(figsize=(6, 6))
sns.heatmap(ax=axs[1], data=confusion_matrix_df_svm, annot=True, fmt="d", cmap='Blues')
axs[1].set_title('Confusion Matrix for NLP SVM')
axs[1].set(xlabel='Predicted',ylabel='Actual')
plt.tight_layout()
plt.show()

print('Classification report for logistic regression:')
print(classification_report(fraud_Y_test,fraud_predictions_lr))
print('Classification report for SVM:')
print(classification_report(fraud_Y_test,fraud_predictions_svm))

NLP MODELS EVALUATION:
WARNING: The purpose of nlp scoring and subsequent models is to provide variables for futher modelling, this is just to ensure that text gave us some useful information in relation with final model's target value
Accuracy: Logistic Regression - 97.95302013422818%, SVM - 97.75167785234899%
Precision: Logistic Regression - 86.37770897832817%, SVM - 78.62796833773086%
Recall: Logistic Regression - 66.74641148325358%, SVM - 71.29186602870813%
F1: Logistic Regression - 75.30364372469634%, SVM - 74.78042659974905%
Area Under ROC: Logistic Regression - 83.11505037903585%, SVM - 85.17069246049347%

<Figure size 600x600 with 0 Axes>

<Figure size 600x600 with 0 Axes>

Classification report for logistic regression:
              precision    recall  f1-score   support

           0       0.98      0.99      0.99      8522
           1       0.86      0.67      0.75       418

    accuracy                           0.98      8940
   macro avg       0.92      0.83      0.87      8940
weighted avg       0.98      0.98      0.98      8940

Classification report for SVM:
              precision    recall  f1-score   support

           0       0.99      0.99      0.99      8522
           1       0.79      0.71      0.75       418

    accuracy                           0.98      8940
   macro avg       0.89      0.85      0.87      8940
weighted avg       0.98      0.98      0.98      8940

#DEEPER ANALYTICS:
print('DEEPER ANALYTICS:')
fraud_probabilities_lr = fraud_model_lr.predict_proba(new_X_test)
fraud_probabilities_svm = fraud_model_svm.predict_proba(new_X_test)
fraud_proba_lr_list = []
for item in fraud_probabilities_lr:
    fraud_proba_lr_list.append(item[1])
fraud_proba_svm_list = []
for item in fraud_probabilities_svm:
    fraud_proba_svm_list.append(item[1])

df_test = pd.DataFrame({'case_no' : fraud_X_test.index,
                                'class' : new_Y_test.to_list(),
                                'prediction_logreg' : fraud_predictions_lr,
                                'prediction_svm' : fraud_predictions_svm,
                                'probability_logreg' : fraud_proba_lr_list,
                                'probability_svm' : fraud_proba_svm_list
                       }, 
                                columns=['case_no','class','prediction_logreg','prediction_svm','probability_logreg','probability_svm'])
df_test.set_index('case_no')
df_positive = df_test[df_test['class']==1]
df_negative = df_test[df_test['class']==0]
print('Logistic Regression:')
print('Average score of negative class : ',df_negative['probability_logreg'].mean())
print('Average score of target class : ',df_positive['probability_logreg'].mean())
print('Median score of negative class : ',df_negative['probability_logreg'].median())
print('Median score of target class : ',df_positive['probability_logreg'].median())
print('Max score of negative class : ',df_negative['probability_logreg'].max())
print('Max score of target class : ',df_positive['probability_logreg'].max())
print('SVM:')
print('Average score of negative class : ',df_negative['probability_svm'].mean())
print('Average score of target class : ',df_positive['probability_svm'].mean())
print('Median score of negative class : ',df_negative['probability_svm'].median())
print('Median score of target class : ',df_positive['probability_svm'].median())
print('Max score of negative class : ',df_negative['probability_svm'].max())
print('Max score of target class : ',df_positive['probability_svm'].max())
print('\n')
print('Logistic Regression deep dive:')
if len(df_positive.loc[df_positive['prediction_logreg']==0]) > 0:
    print('False negatives:')
    print(df_positive.loc[df_positive['prediction_logreg']==0])
else:
    print('False negatives: None!')
if len(df_negative.loc[df_negative['prediction_logreg']==1]) > 0:
    print('False positives:')
    print(df_negative.loc[df_negative['prediction_logreg']==1])
else:
    print('False positives: None!')
print('\n')
df_test_sorted = df_test.sort_values('probability_logreg', ascending = [False])
df_test_sorted['prob_logreg[%]'] = df_test_sorted['probability_logreg'] * 100
df_test_sorted['prob_svm[%]'] = df_test_sorted['probability_svm'] * 100
print('20 cases with highest score in Logistic Regression Model:')
print(df_test_sorted[:20])
print('\n')
print('SVM deep dive:')
if len(df_positive.loc[df_positive['prediction_svm']==0]) > 0:
    print('False negatives:')
    print(df_positive.loc[df_positive['prediction_svm']==0])
else:
    print('False negatives: None!')
if len(df_negative.loc[df_negative['prediction_svm']==1]) > 0:
    print('False positives:')
    print(df_negative.loc[df_negative['prediction_svm']==1])
else:
    print('False positives: None!')
print('\n')

df_test_sorted = df_test.sort_values('probability_svm', ascending = [False])
print('20 cases with highest score in SVM model:')
df_test_sorted[:20]

DEEPER ANALYTICS:
Logistic Regression:
Average score of negative class :  0.019783784657555165
Average score of target class :  0.6316854757360834
Median score of negative class :  0.004792711456937711
Median score of target class :  0.8099896612892235
Max score of negative class :  0.9947409350471352
Max score of target class :  0.9998713321143328
SVM:
Average score of negative class :  0.013473036099519824
Average score of target class :  0.6425339152071416
Median score of negative class :  0.0014594546352741555
Median score of target class :  0.8857184065012893
Max score of negative class :  0.9999947830735267
Max score of target class :  0.9999999999665762


Logistic Regression deep dive:
False negatives:
      case_no  class  prediction_logreg  prediction_svm  probability_logreg  \
20       5579      1                  0               0            0.047767   
267      3147      1                  0               0            0.003469   
276     17586      1                  0               0            0.010671   
366      6088      1                  0               0            0.250266   
376      6993      1                  0               0            0.095378   
...       ...    ...                ...             ...                 ...   
8591     9972      1                  0               1            0.330267   
8740     3645      1                  0               0            0.140591   
8844    10565      1                  0               1            0.220357   
8849     6739      1                  0               0            0.171186   
8879     6975      1                  0               0            0.264887   

      probability_svm  
20           0.018873  
267          0.002174  
276          0.000293  
366          0.314694  
376          0.091181  
...               ...  
8591         0.662768  
8740         0.191431  
8844         0.404866  
8849         0.136385  
8879         0.082582  

[139 rows x 6 columns]
False positives:
      case_no  class  prediction_logreg  prediction_svm  probability_logreg  \
199      7898      0                  1               1            0.620720   
291     16785      0                  1               1            0.587713   
632     16459      0                  1               1            0.935805   
941     11439      0                  1               1            0.780521   
995      4170      0                  1               1            0.983797   
1027     2168      0                  1               1            0.856591   
1171    16823      0                  1               0            0.511147   
1715     1824      0                  1               1            0.865784   
2134    16996      0                  1               1            0.570726   
2162     6514      0                  1               1            0.619188   
2273     4521      0                  1               1            0.723306   
2504     7675      0                  1               1            0.517547   
2861    14666      0                  1               1            0.764290   
3045    12983      0                  1               1            0.650142   
3655    13601      0                  1               1            0.818627   
3926     9544      0                  1               1            0.672597   
4183     6513      0                  1               1            0.810791   
4221    14826      0                  1               1            0.602050   
4248     5343      0                  1               1            0.979021   
4318    11922      0                  1               1            0.954838   
4338     5213      0                  1               1            0.515930   
4764    14466      0                  1               1            0.508428   
4787     9328      0                  1               1            0.641621   
4810     1670      0                  1               0            0.687734   
5010    17402      0                  1               1            0.994741   
5265     6608      0                  1               1            0.601482   
5364    16686      0                  1               1            0.637679   
5521    11121      0                  1               1            0.985674   
6119     1747      0                  1               1            0.723306   
6556     3202      0                  1               1            0.651825   
6559     6727      0                  1               1            0.993490   
6684     6925      0                  1               0            0.619360   
6697     1235      0                  1               1            0.534444   
6921     5474      0                  1               1            0.653405   
7075     9740      0                  1               1            0.549027   
7108     1548      0                  1               0            0.578341   
7177     1157      0                  1               1            0.556707   
7269      661      0                  1               1            0.747162   
7565     8896      0                  1               1            0.615497   
7757     5307      0                  1               1            0.994214   
7961     9773      0                  1               1            0.671064   
8136     3959      0                  1               1            0.763558   
8268     6279      0                  1               0            0.782213   
8622     2986      0                  1               1            0.693324   

      probability_svm  
199          0.341018  
291          0.664845  
632          0.937446  
941          0.853093  
995          0.999982  
1027         0.955313  
1171         0.201705  
1715         0.968854  
2134         0.800006  
2162         0.404052  
2273         0.773510  
2504         0.548123  
2861         0.416174  
3045         0.904300  
3655         0.540849  
3926         0.697577  
4183         0.937159  
4221         0.383821  
4248         0.974431  
4318         0.910242  
4338         0.844763  
4764         0.610035  
4787         0.396284  
4810         0.060014  
5010         0.999995  
5265         0.926513  
5364         0.812075  
5521         0.982040  
6119         0.773510  
6556         0.839749  
6559         0.999991  
6684         0.328949  
6697         0.846481  
6921         0.777778  
7075         0.651539  
7108         0.191049  
7177         0.881281  
7269         0.971606  
7565         0.696534  
7757         0.996190  
7961         0.810178  
8136         0.532451  
8268         0.125745  
8622         0.505272  


20 cases with highest score in Logistic Regression Model:
      case_no  class  prediction_logreg  prediction_svm  probability_logreg  \
4267    17736      1                  1               1            0.999871   
4112    17816      1                  1               1            0.999823   
2049    17640      1                  1               1            0.999611   
567      4833      1                  1               1            0.999064   
1425     5435      1                  1               1            0.999044   
3905    17778      1                  1               1            0.998636   
6613    17536      1                  1               1            0.998370   
5523     5442      1                  1               1            0.997909   
5579     5611      1                  1               1            0.997854   
8497    14129      1                  1               1            0.996891   
8819     8394      1                  1               1            0.996457   
2584    14134      1                  1               1            0.995820   
7396    17330      1                  1               1            0.995542   
1721    17611      1                  1               1            0.995493   
5819     4681      1                  1               1            0.995360   
5010    17402      0                  1               1            0.994741   
2507     5414      1                  1               1            0.994387   
7757     5307      0                  1               1            0.994214   
4696    17714      1                  1               1            0.994162   
8453    15265      1                  1               1            0.993986   

      probability_svm  prob_logreg[%]  prob_svm[%]  
4267         0.999996       99.987133    99.999645  
4112         1.000000       99.982293   100.000000  
2049         1.000000       99.961063   100.000000  
567          1.000000       99.906365    99.999999  
1425         1.000000       99.904394    99.999996  
3905         1.000000       99.863554    99.999980  
6613         1.000000       99.837016    99.999998  
5523         0.999991       99.790892    99.999052  
5579         1.000000       99.785358    99.999996  
8497         1.000000       99.689053    99.999977  
8819         1.000000       99.645687    99.999966  
2584         0.992714       99.582019    99.271391  
7396         0.999999       99.554185    99.999932  
1721         0.999991       99.549318    99.999056  
5819         0.999997       99.536013    99.999652  
5010         0.999995       99.474094    99.999478  
2507         0.994618       99.438652    99.461765  
7757         0.996190       99.421353    99.619009  
4696         0.999984       99.416212    99.998369  
8453         0.992684       99.398623    99.268376  


SVM deep dive:
False negatives:
      case_no  class  prediction_logreg  prediction_svm  probability_logreg  \
20       5579      1                  0               0            0.047767   
267      3147      1                  0               0            0.003469   
276     17586      1                  0               0            0.010671   
366      6088      1                  0               0            0.250266   
376      6993      1                  0               0            0.095378   
...       ...    ...                ...             ...                 ...   
8576     8483      1                  0               0            0.210335   
8704    17331      1                  1               0            0.738532   
8740     3645      1                  0               0            0.140591   
8849     6739      1                  0               0            0.171186   
8879     6975      1                  0               0            0.264887   

      probability_svm  
20           0.018873  
267          0.002174  
276          0.000293  
366          0.314694  
376          0.091181  
...               ...  
8576         0.171734  
8704         0.189369  
8740         0.191431  
8849         0.136385  
8879         0.082582  

[120 rows x 6 columns]
False positives:
      case_no  class  prediction_logreg  prediction_svm  probability_logreg  \
173      1318      0                  0               1            0.427556   
199      7898      0                  1               1            0.620720   
291     16785      0                  1               1            0.587713   
438      9314      0                  0               1            0.092887   
632     16459      0                  1               1            0.935805   
...       ...    ...                ...             ...                 ...   
8448     9029      0                  0               1            0.338407   
8481     1281      0                  0               1            0.243080   
8609    15844      0                  0               1            0.379782   
8622     2986      0                  1               1            0.693324   
8798     3523      0                  0               1            0.258702   

      probability_svm  
173          0.359712  
199          0.341018  
291          0.664845  
438          0.577304  
632          0.937446  
...               ...  
8448         0.554943  
8481         0.550497  
8609         0.414495  
8622         0.505272  
8798         0.403179  

[81 rows x 6 columns]


20 cases with highest score in SVM model:

	case_no	class	prediction_logreg	prediction_svm	probability_logreg	probability_svm
4112	17816	1	1	1	0.999823	1.000000
2049	17640	1	1	1	0.999611	1.000000
567	4833	1	1	1	0.999064	1.000000
6613	17536	1	1	1	0.998370	1.000000
5579	5611	1	1	1	0.997854	1.000000
1425	5435	1	1	1	0.999044	1.000000
3905	17778	1	1	1	0.998636	1.000000
8497	14129	1	1	1	0.996891	1.000000
8819	8394	1	1	1	0.996457	1.000000
7396	17330	1	1	1	0.995542	0.999999
7307	5586	1	1	1	0.980166	0.999998
2503	17618	1	1	1	0.984935	0.999997
5819	4681	1	1	1	0.995360	0.999997
4267	17736	1	1	1	0.999871	0.999996
5010	17402	0	1	1	0.994741	0.999995
6445	10220	1	1	1	0.984397	0.999995
5525	4347	1	1	1	0.986564	0.999993
4866	7659	1	1	1	0.988915	0.999993
1721	17611	1	1	1	0.995493	0.999991
6559	6727	0	1	1	0.993490	0.999991

#Scoring target set using chosen model: 
df_nlp_resampled = fit.transform(df_nlp_score)
nlp_proba_lr = fraud_model_lr.predict_proba(df_nlp_resampled)
nlp_proba_svm = fraud_model_svm.predict_proba(df_nlp_resampled)
nlp_proba_lr_list = []
for item in nlp_proba_lr:
    nlp_proba_lr_list.append(item[1]*100)
nlp_proba_svm_list = []
for item in nlp_proba_svm:
    nlp_proba_svm_list.append(item[1]*100)

df_nlp_models_add = pd.DataFrame({'case_no' : df_nlp_score.index,
                                'score_logreg' : nlp_proba_lr_list,
                                'score_svm' : nlp_proba_svm_list
                       }, 
                                columns=['case_no','score_logreg','score_svm'])
df_nlp_models_add = df_nlp_models_add.set_index('case_no')

df_target = df_target.join(df_nlp_models_add[['score_logreg','score_svm']])

#Saving CSV with processed dataframe:
df_target.to_csv('df_after_nlp.csv', sep=";", encoding='utf-8')

#closer look on variable connected with similarity:
df_target[df_target['is_similar']==1]

	telecommuting	has_company_logo	has_questions	missing_sum	salary	employment_group_Other	employment_group_Full-time	employment_group_Part-time	employment_group_Temporary	required_experience_Internship	required_experience_Not Applicable	required_experience_no data	required_experience_Mid-Senior level	required_experience_Associate	required_experience_Entry level	required_experience_Executive	required_experience_Director	education_Mid Risk	education_Low Risk	education_High Risk	education_Other	education_Super Risk	region_Low-Mid Risk	region_Zero Risk	region_Low Risk	region_High-Mid Risk	region_Mid Risk	region_High Risk	#fraudulent	is_similar	failed_perc	unique_perc	word_count	score_logreg	score_svm
job_id
17264	0	1	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	1	23.427332	0.000000	461	1.186836	0.538866
7805	0	1	1	2	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1	21.691176	0.000000	272	1.467835	0.504773
17754	0	0	0	2	2	0	1	0	0	0	1	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	1	1	17.948718	0.000000	78	91.430557	89.333581
13788	1	1	0	3	0	0	1	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	1	22.292994	0.000000	157	0.102939	0.003576
11607	0	1	0	2	0	0	1	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	1	0	0	0	0	1	18.126888	0.000000	331	1.215002	0.284753
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
8532	0	1	1	2	0	1	0	0	0	0	0	1	0	0	0	0	0	1	0	0	0	0	0	0	1	0	0	0	0	1	19.503546	0.000000	282	4.434075	1.489110
17589	0	0	0	1	7	0	1	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	0	1	1	22.368421	0.000000	152	94.528863	92.985864
2419	0	1	0	2	0	0	1	0	0	0	0	0	0	0	1	0	0	1	0	0	0	0	1	0	0	0	0	0	0	1	21.911422	0.000000	429	0.078943	0.014235
1400	0	1	1	1	0	1	0	0	0	1	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	0	0	0	1	30.405405	0.337838	296	0.377522	0.035958
10624	0	1	1	0	5	0	1	0	0	0	0	0	0	1	0	0	0	0	1	0	0	0	0	0	0	0	1	0	0	1	24.615385	0.000000	520	1.071755	0.425305

1212 rows × 35 columns